Passing — Page 7

Is good luck driving the low interception rates of Joe Flacco and Colin Kaepernick?

by Chase Stuart on January 28, 2013

in History, Passing, Quarterbacks, Statgeekery, Theory

Flaccoing?

In September, I started a post by asking you to make this assumption:

Assume that it is within a quarterback’s control as to whether or not he throws a completed pass on any given pass attempt. However, if he throws an incomplete pass, then he has no control over whether or not that pass is intercepted.

If that assumption is true, that would mean all incomplete pass attempts could be labeled as “passes in play” for the defense to intercept. Therefore, a quarterback’s average number of “Picks On Passes In Play” (or POPIP) — that is, the number of interceptions per incomplete pass he throws — is out of his control.

After doing the legwork to test that assumption, I reached two conclusions. One, interception rate is just really random, and predicting it is a fool’s errand. Two, using a normalized INT rate — essentially replacing a quarterback’s number of interceptions per incomplete pass with the league average number of interceptions per incomplete pass — was a slightly better predictor of future INT rate than actual INT rate. It’s not a slam dunk, but there is some merit to using POPIP, because completion percentage, on average, is a better predictor of future INT rate than current INT rate.

So, why am I bringing this up today, at the start of Super Bowl week? Take a look at where Sunday’s starting quarterbacks ranked this year in POPIP (playoff statistics included, minimum 250 pass attempts):
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Tagged as: 49ers, Colin Kaepernick, Donovan McNabb, Joe Flacco, POPIP, Ravens

{ 14 comments }

NFL Passing since 1950 (in graphic form)

by Chase Stuart on January 25, 2013

in Checkdowns, Data Dump, History, Passing

Want to see how passing has changed in the NFL over the last 63 years? A picture is worth at least 1,000 words in this case. The graph below shows the number of interceptions per dropback (red), sacks per dropback (purple), non-INT incomplete passes per dropback (yellow) and completions per dropback (green). Of course, a dropback is simply a pass attempt or a sack. The information is stacked on top of each other for ease of viewing.

[continue reading…]

{ 6 comments }

Charting Eli Manning’s career, in five and ten game increments

by Chase Stuart on January 25, 2013

in Passing, Quarterbacks

In October 2009, Neil Paine wrote that Eli Manning had seemingly turned the corner, starting with the five-game stretch from week 17 of the 2007 season that ended in the Super Bowl. And since that post, Manning has been even better, with his 2011 season standing out as the best year of his career. I thought it would be fun to chart Eli’s career game-by-game according to ANY/A. Actually, since that chart would be incredibly volatile, I’m going to do it in five- and ten-game increments.

The chart below shows the average of Manning’s ANY/A in each of his last five games (playoffs included) beginning with the fifth game of his career in 2004. Of note: the black line represents the league average ANY/A (which, if we’re talking about the last 2 games of Year N and the first 3 games of Year N+1, is 40% of the Year N league average and 60% of the Year N+1 league average), and the two big purple dots show the two Super Bowl victories (or, more accurately, the Super Bowl win, the prior three playoff wins, and the week 17 game).

[continue reading…]

Tagged as: Eli Manning, Giants, Super Bowl

{ 1 comment }

Is Joe Flacco elite?

by Chase Stuart on January 22, 2013

in History, Passing, Statistics

Just a guess, but I think that question will be asked quite a few times over the next couple of weeks. While the inanity of the discussion that usually follows that question is not something I wish to emulate, there’s no particular reason not to take an in-depth look at Flacco’s career. The table below shows Flacco’s performance in six key metrics — all relative to league average (1.00) — for each season of his career:

As you can see, with the exception of his great interception rate — which justifies its own post during this pre-Super Bowl period — Flacco’s career performance has been rather average. His touchdown rate, like those of many quarterbacks, has bounced up and down throughout his career. His sack rate was below average during his first three years, improved significantly in 2011, and landed right at the league average in 2012.

That is an elite Fu Manchu.

In the three main statistics — Y/A, NY/A, and ANY/A — Flacco has consistently finished in a tight window around the league average. His ANY/A has been slightly better than his NY/A thanks to that lofty interception rate, but suffice it to say Joe Flacco is, and has been for years, a league average quarterback.

If we look at ESPN’s Total QBR, Flacco ranked 27th as a rookie in 2008, 15th in 2009, and 12th in 2010, signaling a young quarterback improving and on the rise. In 2011, he ranked 14th, perhaps signaling a leveling off, and then this past season, he finished 25th. The positive spin would be that he’s a league-average quarterback, and the negative one (at least prior to this post-season) would have been that he was regressing.

On the other hand, here is how Flacco has performed in the playoffs in each game, as measured by AY/A:

[continue reading…]

Tagged as: Jake Delhomme, Joe Flacco, Joe Montana, Playoffs, Ravens

{ 12 comments }

Checkdowns: Career passing stats in wins and losses

by Chase Stuart on January 5, 2013

in Checkdowns, History, Passing

Is this a thinly-veiled Brady/Manning post?

Last weekend, I looked at career rushing stats in wins and losses; today I will do the same but for quarterbacks.

I looked at all games, including playoffs, from 1960 to 2011, for all quarterbacks with at least 5,000 career passing yards over that time period. The table below lists the following information for each passer:

– His first year (or 1960, if he played before 1960) and his last year (or 2011, if still active)
– All the franchises he played for (which you can search for in the search box)
– His number of career wins, and his touchdown rate, interception rate, yards per attempt and Adjusted Yards per Attempt (which includes a 20-yard bonus for touchdown passes and a 45-yard penalty for interceptions) in wins ^[1]Unfortunately, I excluded sack data from this study due to its general unavailability for most of the covered time period.
– His number of career losses, and his touchdown rate, interception rate, yards per attempt and Adjusted Yards per Attempt in losses

The table is sorted by AY/A in wins; unsurprisingly, Aaron Rodgers — who is the career leader in that metric — tops this table, too. In fact, Rodgers is also the leader in AY/A in losses. Note that this table includes all games played by the quarterback, not just his starts.

Rk	Player	Years	Teams	PYD	Win	TD%_W	INT%_W	Y/A_W	AY/A_W	Loss	TD%_L	INT%_L	Y/A_L	AY/A_L
1	Aaron Rodgers	2005--2011	gnb	19147	49	7.6%	1.3%	8.7	8.3	27	4.3%	2.5%	7.4	6.4
2	Matt Schaub	2004--2011	atl-htx	17936	48	5.3%	1.7%	8.7	8.1	53	3.5%	3.3%	7.2	5.8
3	Tony Romo	2005--2011	dal	21666	60	6.6%	2.1%	8.7	7.9	43	4.3%	3.4%	7	5.5
4	Kurt Warner	1998--2009	ram-nyg-crd	36296	81	6.8%	2.2%	8.7	7.8	57	3.3%	4.4%	7.2	5.3
5	Daunte Culpepper	1999--2009	min-mia-rai-det	25133	45	7.1%	2.2%	8.7	7.8	64	3.3%	4%	6.9	5.1
6	Bob Berry	1965--1975	min-atl	9197	32	7.4%	2.3%	8.6	7.7	36	4.2%	7.4%	7.1	3.8
7	Steve Young	1985--1999	tam-sfo	36450	125	6.8%	1.7%	8.3	7.6	60	2.9%	4.2%	7.2	5.3
8	Philip Rivers	2004--2011	sdg	26105	69	6.2%	2.3%	8.5	7.6	39	4%	3.1%	7.3	6
9	Ben Roethlisberger	2004--2011	pit	29729	90	5.7%	2.2%	8.4	7.6	38	3.7%	4.9%	7.2	5
10	John Friesz	1990--2000	sdg-was-sea-nwe	8699	19	5%	1%	7.8	7.5	38	2.6%	4%	5.8	4
11	Bart Starr	1960--1971	gnb	22810	99	6.6%	2.9%	8.6	7.5	41	2.4%	5.9%	6.7	4.1
12	Don Meredith	1960--1968	dal	17750	51	8.5%	3.3%	8.8	7.5	50	3.5%	6%	6.2	3.6
13	Drew Brees	2001--2011	sdg-nor	43722	97	6.5%	1.7%	8	7.4	66	3.4%	3.7%	6.7	5.1
14	Ken O'Brien	1984--1993	nyj-phi	25598	56	5.8%	1.7%	8	7.4	72	2.1%	3.6%	6.3	4.7
15	J.P. Losman	2004--2011	buf-rai-mia	6271	17	5.8%	1.5%	7.9	7.4	28	2.5%	4.4%	6.1	4.1
16	Trent Green	1997--2008	was-ram-kan-mia	28794	59	5.3%	2.1%	8.2	7.3	63	3.6%	3.8%	7.1	5.5
17	Rob Johnson	1995--2003	jax-buf-tam-was-rai	5947	20	4.8%	1.5%	7.9	7.3	25	2.8%	3.6%	6.7	5.1
18	Chad Pennington	2000--2010	nyj-mia	19241	46	5.1%	1.2%	7.7	7.3	49	3.2%	4.1%	6.6	4.9
19	Boomer Esiason	1984--1997	cin-nyj-crd	38520	89	6.6%	2.4%	8.2	7.3	103	3.3%	4.4%	6.5	4.6
20	Neil Lomax	1981--1988	crd	23156	48	6.4%	2.1%	8.1	7.3	59	3%	3.3%	6.6	5.2
21	David Garrard	2002--2010	jax	16489	45	5.3%	1.4%	7.8	7.3	44	2.7%	3.4%	6.4	4.9
22	Matthew Stafford	2009--2011	det	8220	13	8.1%	1.8%	7.9	7.2	17	3.4%	4.4%	6.3	4.4
23	Joe Montana	1979--1994	sfo-kan	46323	140	6.4%	2.2%	8.1	7.2	60	2.7%	3.4%	6.3	4.9
24	Eddie LeBaron	1960--1963	dal	5331	11	12.5%	5.5%	9.4	7.2	31	4.7%	8.7%	7.1	3.3
25	Peyton Manning	1998--2010	clt	60217	150	6.3%	1.9%	8	7.2	77	3.9%	4.1%	6.9	5.2
26	Ed Brown	1960--1965	chi-pit-clt	7723	35	7.7%	5.8%	9.7	7.2	33	2.9%	8.8%	6.5	2.6
27	Wade Wilson	1981--1998	min-atl-nor-dal-rai	18605	66	6.1%	2.6%	8.3	7.2	63	2.4%	5.3%	6.2	3.9
28	Jay Cutler	2006--2011	den-chi	18637	42	6.6%	2.2%	8.1	7.2	38	2.7%	4.6%	6.5	4.5
29	Josh Freeman	2009--2011	tam	8898	17	5.6%	1.8%	7.9	7.2	24	2.8%	4.6%	6.1	4.1
30	Tom Brady	2000--2011	nwe	45264	140	6.1%	1.6%	7.8	7.2	43	3.6%	4.2%	6.3	4.5
31	Matt Moore	2007--2011	car-mia	5137	17	6.2%	1.8%	7.8	7.1	19	2.8%	5%	6.2	4
32	Chris Chandler	1988--2004	clt-tam-crd-ram-oti-atl-chi	29212	72	5.9%	2.6%	8.2	7.1	105	3.1%	4.4%	6.4	4.4
33	Len Dawson	1960--1975	cle-kan	30112	105	8.7%	3.6%	8.6	7.1	64	3.2%	6.3%	6.6	3.8
34	Joe Flacco	2008--2011	rav	15348	49	4.6%	1.2%	7.6	7.1	24	3%	4.4%	5.9	4
35	Trent Edwards	2007--2010	buf-jax	6019	14	4%	1.6%	7.7	7.1	22	2%	4.3%	5.7	3.8
36	Jeff Garcia	1999--2009	sfo-cle-det-phi-tam	26894	63	5.4%	1.3%	7.5	7.1	68	3.4%	3.1%	6.4	5.1
37	Ken Anderson	1971--1986	cin	34159	100	6.2%	2.4%	8	7.1	92	2.7%	4.7%	6.7	4.7
38	Rudy Bukich	1960--1968	pit-chi	7865	30	7.5%	3.5%	8.5	7	35	3.5%	8.6%	6	2.3
39	Troy Aikman	1989--2000	dal	36791	105	4.8%	2.1%	7.9	7	76	2.1%	4.1%	6	4.2
40	Damon Huard	1998--2008	mia-nwe-kan	6349	20	4.9%	1.1%	7.4	7	24	2%	4.3%	5.8	4
41	Jim Everett	1986--1997	ram-nor-sdg	35957	66	5.7%	2.6%	8.1	7	97	3.2%	4.2%	6.5	4.6
42	Roger Staubach	1969--1979	dal	25491	106	6.1%	2.5%	8	7	44	3.5%	6.3%	6.7	3.9
43	Bert Jones	1973--1982	clt-ram	18589	47	6.4%	3.1%	8.2	7	58	3.6%	4.6%	6.3	4.3
44	Frank Reich	1985--1998	buf-car-nyj-det	6858	39	8.8%	2.1%	7.7	7	39	3.3%	4.3%	6.3	4.4
45	Jeff Hostetler	1986--1997	nyg-rai-was	17464	70	5.5%	1.9%	7.7	7	40	2.3%	4.1%	6.3	4.5
46	Dan Fouts	1973--1987	sdg	45165	91	5.9%	3.2%	8.3	6.9	95	3.1%	5.5%	7.1	4.7
47	Bill Kenney	1980--1988	kan	17374	37	5.9%	2.5%	8	6.9	49	3.2%	4.2%	6.5	4.6
48	Y.A. Tittle	1960--1964	sfo-nyg	11542	40	8.9%	4.3%	8.7	6.9	23	2.5%	6.9%	5.7	2.7
49	Mark Brunell	1994--2011	gnb-jax-was-nor-nyj	33905	99	4.8%	1.8%	7.6	6.9	91	3.2%	2.9%	6.2	4.9
50	Aaron Brooks	2000--2006	nor-rai	20822	41	5.8%	1.6%	7.5	6.9	54	3.3%	4.1%	6.4	4.7
51	Patrick Ramsey	2002--2008	was-nyj-den	5929	16	5.2%	2.3%	7.8	6.9	24	3.1%	3.8%	5.8	4.2
52	Scott Mitchell	1992--2001	mia-det-rav-cin	15925	40	6%	2.1%	7.7	6.9	45	2.6%	4.6%	5.9	3.9
53	Randy Wright	1984--1988	gnb	7106	12	5.4%	3.4%	8.3	6.9	33	2.2%	5.5%	5.9	3.5
54	Rich Gannon	1987--2004	min-was-kan-rai	30434	91	5.5%	1.5%	7.4	6.9	71	3%	3.6%	6.2	4.6
55	Earl Morrall	1960--1976	det-nyg-clt-mia	17529	92	7.9%	4.8%	8.9	6.9	44	4.2%	6.9%	6.6	3.6
56	Sonny Jurgensen	1960--1974	phi-was	31546	74	7.7%	3.9%	8.4	6.9	79	4.5%	4.9%	6.8	4.7
57	Steve DeBerg	1978--1998	sfo-den-tam-kan-mia-atl	34752	72	5.4%	2.3%	7.8	6.9	114	3.2%	4.9%	6.4	4.2
58	Steve Beuerlein	1988--2003	rai-dal-crd-jax-car-den	24317	64	5.6%	2.3%	7.8	6.8	66	3.4%	4.2%	6.8	5
59	Fran Tarkenton	1961--1978	min-nyg	48806	131	6.8%	2.8%	8	6.8	117	3.6%	5.5%	6.5	4.1
60	John Brodie	1960--1973	sfo	30783	78	6.7%	3.3%	8.2	6.8	79	3.3%	6%	6.1	3.5
61	Doug Flutie	1986--2005	chi-nwe-buf-sdg	15209	48	5.2%	2.4%	7.8	6.8	45	2.9%	3.9%	6	4.3
62	Johnny Unitas	1960--1973	clt-sdg	32335	107	6.3%	3.8%	8.4	6.8	59	2.7%	7.3%	6.5	3.2
63	Joe Namath	1965--1977	nyj-ram	28299	68	6.4%	4%	8.5	6.8	71	3.3%	6.8%	6.5	3.5
64	Matt Ryan	2008--2011	atl	14832	43	6.1%	1.9%	7.5	6.8	22	2.4%	3%	6.1	4.8
65	Craig Erickson	1992--1997	tam-clt-mia	7625	18	4.8%	2.7%	7.9	6.8	34	3.2%	3.9%	6.5	4.8
66	Marc Bulger	2002--2009	ram	23758	42	4.9%	2.6%	7.8	6.8	57	3.1%	3.3%	6.8	5.4
67	Matt Cassel	2005--2011	nwe-kan	11769	42	5.1%	2%	7.6	6.8	30	3.5%	3.3%	5.7	4.3
68	Tom Flores	1960--1969	rai-buf-kan	11960	40	8.3%	3.8%	8.3	6.8	44	2.8%	6.7%	5.7	2.8
69	Phil Simms	1979--1993	nyg	35141	102	5.3%	2.5%	7.7	6.7	72	3%	4.3%	6.4	4.6
70	Derek Anderson	2006--2011	cle-crd-car	9148	21	5.5%	2.4%	7.7	6.7	32	2.7%	4.6%	5.7	3.6
71	Michael Vick	2001--2011	atl-phi	18889	65	5.8%	2.4%	7.7	6.7	51	2.8%	3.4%	6.3	4.9
72	Brett Favre	1991--2010	atl-gnb-nyj-min	77693	201	6.3%	2.2%	7.6	6.7	125	3.2%	4.9%	6.4	4.3
73	Craig Morton	1965--1982	dal-nyg-den	29143	118	6.7%	3.7%	8.2	6.7	82	2.6%	6.5%	6.2	3.4
74	Steve Pelluer	1985--1990	dal-kan	6870	17	3.3%	2.2%	7.6	6.7	26	2.9%	4.7%	6.9	4.8
75	Dan Marino	1983--1999	mia	65871	155	5.7%	2.4%	7.7	6.7	105	4.1%	3.9%	6.8	5.1
76	Donovan McNabb	1999--2011	phi-was-min	40859	106	5.4%	2%	7.4	6.7	74	2.9%	2.6%	6.1	5
77	Dave Krieg	1980--1998	sea-kan-det-crd-chi-oti	40042	113	6.7%	3%	7.9	6.7	98	3%	4.4%	6.5	4.5
78	Warren Moon	1984--2000	oti-min-sea-kan	52195	108	5.5%	2.6%	7.7	6.6	110	3.1%	4.2%	6.8	4.9
79	Jim Kelly	1986--1996	buf	39330	110	6.1%	3.2%	8	6.6	67	3.1%	4.6%	6.6	4.6
80	John Hadl	1962--1977	sdg-ram-gnb-oti	33941	103	7%	3.7%	8.2	6.6	92	3.3%	7.8%	6.1	2.7
81	Bernie Kosar	1985--1996	cle-dal-mia	25254	67	4.8%	1.9%	7.4	6.6	66	3.1%	3.4%	6.6	5.1
82	Jake Delhomme	1999--2011	nor-car-cle-htx	22822	65	5.5%	2.9%	7.8	6.6	45	3.1%	4.2%	6.6	4.8
83	Vince Evans	1977--1995	chi-rai	9511	37	7.1%	3.8%	8.2	6.6	57	2.4%	6%	6.3	3.6
84	John Elway	1983--1998	den	56439	163	5%	2.6%	7.7	6.6	92	2.8%	3.9%	6.3	4.6
85	Drew Bledsoe	1993--2006	nwe-buf-dal	45946	102	5.1%	1.9%	7.4	6.6	99	2.4%	4.2%	5.9	4
86	Jason Campbell	2006--2011	was-rai	14417	32	3.8%	1.7%	7.3	6.6	39	3.3%	2.7%	6.4	5.3
87	Pete Liske	1964--1972	nyj-den-phi	5170	16	7%	2.6%	7.6	6.6	23	2.2%	8.2%	5.9	2.3
88	Jeff George	1990--2001	clt-atl-rai-min-was	28603	48	5.5%	2.7%	7.7	6.6	85	3.2%	2.9%	6.6	5.4
89	Alex Smith	2005--2011	sfo	13038	33	4.4%	1.1%	7	6.6	39	2.9%	4.3%	6	4.1
90	Jim Zorn	1976--1987	sea-gnb-tam	21249	52	4.9%	2.9%	7.8	6.6	68	2.8%	5.4%	6.1	3.7
91	Lynn Dickey	1971--1985	oti-gnb	23914	52	6.5%	4.4%	8.4	6.6	76	3.5%	6.6%	7	4.1
92	Jon Kitna	1997--2011	sea-cin-det-dal	30104	56	5.7%	2%	7.4	6.6	86	2.8%	4.7%	6.3	4.3
93	Eric Hipple	1981--1989	det	11009	30	6.3%	3%	7.8	6.6	36	1.8%	5.5%	6.4	4
94	Bob Griese	1967--1980	mia	26559	108	7.4%	3.9%	8.1	6.5	62	3.5%	6.4%	6.4	3.5
95	Chris Miller	1987--1999	atl-ram-den	19789	37	5.7%	2.4%	7.5	6.5	63	3.6%	4.2%	6.3	4.5
96	Gus Frerotte	1994--2008	was-det-den-cin-min-mia-ram	21666	58	5.1%	2.7%	7.6	6.5	60	2.5%	4.1%	6.2	4.4
97	Matt Hasselbeck	1999--2011	gnb-sea-oti	35891	91	5.1%	2.4%	7.5	6.5	80	3%	3.4%	6.3	4.8
98	Tarvaris Jackson	2006--2011	min-sea	7239	27	4.5%	3.1%	7.8	6.5	23	2.8%	3.4%	5.8	4.3
99	Jeff Blake	1992--2005	nyj-cin-nor-rav-crd-phi-chi	21711	42	5.1%	2.1%	7.4	6.5	77	3.6%	3.6%	6.3	4.7
100	Tony Eason	1983--1990	nwe-nyj	11703	35	5.1%	2.8%	7.7	6.5	31	3.3%	3.4%	6.7	5.2
101	Jim Harbaugh	1987--2000	chi-clt-rav-sdg	27194	78	4.8%	2.1%	7.3	6.5	93	2.3%	3.6%	6.2	4.6
102	Don Majkowski	1987--1996	gnb-clt-det	12906	34	4.8%	2.8%	7.7	6.5	43	2.6%	4.2%	6	4.2
103	Gary Hogeboom	1982--1989	dal-clt-crd	9598	31	5.1%	2.6%	7.5	6.5	28	2.7%	6.1%	6.7	4
104	Joe Theismann	1974--1985	was	26988	95	6%	2.8%	7.6	6.5	59	2.4%	5.1%	6.3	4.1
105	Randall Cunningham	1985--2001	phi-min-dal-rav	32405	98	6.1%	2.6%	7.6	6.5	73	3.1%	3.6%	6.3	4.7
106	Byron Leftwich	2003--2010	jax-atl-pit-tam	10439	30	5%	1.6%	7.1	6.5	31	2.6%	3.5%	6.2	4.7
107	Tony Banks	1996--2005	ram-rav-was-htx	15315	43	5.2%	2.2%	7.4	6.5	52	2%	3.7%	5.9	4.3
108	Bobby Hebert	1985--1996	nor-atl	22331	63	5.2%	3%	7.7	6.5	55	3.5%	5%	6.2	4.1
109	Greg Landry	1968--1984	det-clt-chi	16100	55	6.7%	3.9%	8.1	6.5	65	2.5%	4.7%	6.3	4.2
110	Eli Manning	2004--2011	nyg	30095	77	5.5%	2.2%	7.3	6.4	54	3.7%	4.5%	6.7	4.7
111	Jay Fiedler	1998--2005	min-jax-mia-nyj	12499	50	5%	2.6%	7.5	6.4	29	2.5%	5.9%	6	3.4
112	Stan Humphries	1989--1997	was-sdg	18538	55	4.4%	2.3%	7.4	6.4	39	2.2%	5.1%	5.9	3.7
113	Jim Plunkett	1971--1986	nwe-sfo-rai	28175	85	5.6%	3.4%	7.9	6.4	82	3.2%	7.1%	6.4	3.2
114	Elvis Grbac	1994--2001	sfo-kan-rav	17492	61	4.8%	2.4%	7.4	6.4	39	3.1%	4.4%	6.2	4.3
115	Richard Todd	1976--1985	nyj-nor	21636	51	5.2%	3.6%	7.9	6.4	70	3.2%	7%	6.2	3.1
116	Steve Grogan	1975--1990	nwe	27457	80	6.7%	4.3%	8.2	6.4	71	3.5%	7.2%	6.8	3.6
117	Frank Ryan	1960--1970	ram-cle-was	15833	66	9.3%	4.4%	8.2	6.4	42	4%	6.1%	6.6	3.9
118	Carson Palmer	2004--2011	cin-rai	25659	50	5.9%	2.9%	7.6	6.4	59	3.8%	3.5%	6.9	5.3
119	Shaun Hill	2005--2011	min-sfo-det	6209	18	5.5%	1.8%	7.1	6.4	16	3.2%	2.8%	6.3	5.1
120	Mark Rypien	1988--2001	was-cle-ram-phi-clt	20249	58	5.7%	3.3%	7.7	6.4	47	2.9%	3.6%	6.5	4.9
121	Bubby Brister	1986--2000	pit-phi-nyj-den-min	14801	47	5.7%	2.3%	7.3	6.4	51	1.9%	4.3%	5.9	3.9
122	Kerry Collins	1995--2011	car-nor-nyg-rai-oti-clt	42478	92	4.4%	2.1%	7.2	6.4	113	2.7%	4%	6.1	4.3
123	Steve McNair	1995--2007	oti-rav	33068	100	4.6%	2.1%	7.2	6.4	72	2.6%	3.4%	6.4	4.9
124	Charlie Batch	1998--2011	det-pit	10610	40	5.2%	2.8%	7.5	6.3	37	3.1%	3.4%	6.6	5.1
125	Bill Nelsen	1963--1972	pit-cle	15004	46	6.5%	4.1%	8	6.3	43	3%	7.2%	6.5	3.4
126	Charley Johnson	1961--1975	crd-oti-den	24410	68	7.3%	4.7%	8.3	6.3	70	3%	5.9%	6.3	3.6
127	Steve Bartkowski	1975--1986	atl-ram	24916	60	5.9%	3.1%	7.6	6.3	73	3.5%	5.2%	6.5	4.3
128	Sam Bradford	2010--2011	ram	5676	8	4.1%	1.5%	6.9	6.3	18	1.9%	2.5%	5.6	4.5
129	Gary Danielson	1977--1988	det-cle	14000	42	4.9%	2.9%	7.5	6.3	43	3.5%	5.3%	6.7	4.4
130	Brian Sipe	1974--1983	cle	23896	60	6%	3.2%	7.6	6.3	62	3%	5.4%	6.2	3.8
131	Jay Schroeder	1985--1994	was-rai-cin-crd	20854	71	5.2%	2.7%	7.4	6.3	50	2.7%	5.3%	6.6	4.3
132	Virgil Carter	1968--1976	chi-cin-sdg	5127	21	5.7%	3%	7.5	6.3	24	2.1%	4.7%	5.6	3.5
133	Tommy Kramer	1977--1990	min-nor	25651	64	5.9%	2.8%	7.4	6.3	66	2.9%	5.7%	6.2	3.7
134	Brad Johnson	1994--2008	min-was-tam-dal	30457	102	4.6%	2.1%	7.1	6.2	70	2.9%	3.9%	6.2	4.5
135	Kelly Holcomb	1995--2007	tam-clt-cle-buf-min	6453	9	5.5%	3.4%	7.7	6.2	29	4%	4.5%	6.5	4.6
136	Quincy Carter	2001--2004	dal-nyj	6491	20	4.7%	2.2%	7.1	6.2	18	1.8%	5.3%	5.9	3.5
137	Ryan Fitzpatrick	2005--2011	ram-cin-buf	10936	22	6.2%	2.4%	7.2	6.2	34	2.9%	4.5%	5.9	3.9
138	Neil O'Donnell	1991--2003	pit-nyj-cin-oti	23399	72	5%	2%	7	6.2	58	2.5%	2.3%	6.3	5.4
139	James Harris	1969--1979	buf-ram-sdg	8479	44	5.8%	4.2%	8	6.2	34	1.8%	6.6%	6	3.1
140	Brian Griese	1998--2008	den-mia-tam-chi	19440	53	5.2%	2.8%	7.4	6.2	40	3.3%	4.2%	6.6	4.7
141	Terry Bradshaw	1970--1983	pit	31822	125	7%	4.3%	8	6.2	62	3%	7.3%	6.1	2.9
142	Bill Munson	1964--1979	ram-det-sea-sdg-buf	12940	41	6.4%	2.6%	7.2	6.2	58	2.8%	5%	6.1	3.9
143	Steve Tensi	1966--1970	sdg-den	5558	15	8.5%	4.4%	8	6.1	29	3.5%	5.7%	5.8	3.3
144	Jeff Kemp	1981--1991	ram-sfo-sea-phi	6403	28	6.7%	2.9%	7.3	6.1	26	1.9%	5.5%	6.3	3.8
145	Ty Detmer	1993--2001	gnb-phi-sfo-cle-det	6499	18	4.9%	2.5%	7.1	6.1	24	2.7%	4.6%	6.5	4.4
146	Billy Wade	1960--1966	ram-chi	11390	34	6.1%	3.5%	7.6	6.1	33	3.8%	6.3%	6.4	3.7
147	Dave M. Brown	1992--2000	nyg-crd	10304	29	4.1%	2.5%	7.2	6.1	42	1.9%	4.2%	5.8	4
148	Mark Sanchez	2009--2011	nyj	10364	30	5.1%	2%	6.9	6.1	22	2.9%	5%	6.2	4
149	Joe Ferguson	1973--1990	buf-det-tam-clt	30631	83	6.4%	3.1%	7.4	6.1	107	3%	5.8%	6.1	3.5
150	Norm Snead	1961--1976	was-phi-min-nyg-sfo	30797	57	6.9%	4.3%	7.9	6.1	114	3.5%	6.7%	6.7	3.7
151	Dennis Shaw	1970--1975	buf-crd	6347	12	5.9%	5.3%	8.4	6.1	34	2.8%	8.1%	6.5	2.9
152	Vince Ferragamo	1977--1986	ram-buf-gnb	12564	35	7.1%	3.7%	7.6	6.1	42	2.9%	7.1%	6.5	3.4
153	Jake Plummer	1997--2006	crd-den	30593	74	4.7%	2.5%	7.1	6.1	75	2.9%	4.8%	6.4	4.3
154	Tommy Maddox	1992--2005	den-ram-nyg-pit	8754	27	5.9%	3.2%	7.4	6.1	28	2.6%	5.3%	6.1	3.7
155	Daryle Lamonica	1963--1974	buf-rai	21082	104	7.8%	4.6%	8	6.1	37	3%	7.3%	6	2.8
156	Kyle Orton	2005--2011	chi-den-kan	14532	36	4.5%	1.9%	6.8	6.1	35	3%	3.1%	6.4	5
157	Roman Gabriel	1962--1977	ram-phi	29780	87	5.7%	2.6%	7.1	6.1	79	3.2%	4%	5.8	4.1
158	Bob Lee	1969--1980	min-atl-ram	5416	60	5.9%	4.8%	8.1	6.1	24	1.2%	6.2%	5	2.3
159	David Carr	2002--2010	htx-car-nyg-sfo	14433	32	3.4%	2.2%	7	6.1	61	2.7%	3.4%	6.2	4.7
160	Jack Trudeau	1986--1995	clt-nyj-car	10494	25	3.2%	2.4%	7.1	6	43	2.3%	5.2%	5.8	3.5
161	Steve Fuller	1979--1986	kan-chi	7454	33	4%	3.5%	7.5	6	29	1.9%	4%	6.2	4.5
162	Danny White	1976--1988	dal	24243	124	5.8%	4%	7.7	6	59	4%	5.3%	6.7	4.4
163	Archie Manning	1971--1984	nor-oti-min	23911	37	4.4%	3.2%	7.4	6	110	3.1%	5.1%	6.3	4.1
164	Ken Stabler	1970--1984	rai-oti-nor	30579	110	6.6%	4.6%	7.9	6	64	3%	7.3%	6.5	3.3
165	Doug Williams	1978--1989	tam-was	18108	49	5.4%	2.8%	7.2	6	45	3.1%	4.8%	6.5	4.4
166	Joe Pisarcik	1977--1984	nyg-phi	5552	25	4.6%	4.1%	7.8	6	32	2.1%	5.7%	5.7	3.1
167	Jim McMahon	1982--1996	chi-sdg-phi-min-crd-gnb	19260	86	4.5%	3.3%	7.4	6	40	2.6%	3.8%	6.4	4.8
168	Milt Plum	1960--1969	cle-det-ram-nyg	13335	46	6.9%	4.9%	8.1	6	40	3.1%	6%	6.3	3.7
169	Ron Jaworski	1974--1989	ram-phi-mia-kan	29859	89	5.4%	2.9%	7.2	6	79	3.4%	4.8%	6.5	4.4
170	Rodney Peete	1989--2004	det-dal-phi-was-car	16636	55	4.3%	3.4%	7.5	6	48	2.2%	4.3%	6.5	4.6
171	Vinny Testaverde	1987--2007	tam-cle-rav-nyj-dal-nwe-car	47553	102	5.3%	3.1%	7.3	6	137	3.3%	4.5%	6.7	4.7
172	Billy Kilmer	1961--1978	sfo-nor-was	21555	88	6.7%	3.7%	7.5	6	81	3.3%	5.9%	6.1	3.5
173	Tim Couch	1999--2003	cle	11131	22	5.5%	3.2%	7.3	6	40	2.7%	4.3%	6	4.1
174	Erik Kramer	1987--1999	atl-det-chi-sdg	16336	38	4.9%	2.4%	7	6	48	3.4%	4.1%	6.5	4.7
175	Trent Dilfer	1994--2007	tam-rav-sea-cle-sfo	21489	68	5.3%	2.7%	7.1	6	65	2%	5.1%	6	3.7
176	Mike Pagel	1982--1993	clt-cle-ram	9593	22	4.5%	2.6%	7.1	6	53	2.9%	4.9%	6	3.8
177	Kordell Stewart	1995--2005	pit-chi-rav	15490	76	3.5%	2.1%	6.8	5.9	54	2.7%	5.6%	5.5	3
178	Chad Henne	2008--2011	mia	7114	14	3.6%	1.7%	6.6	5.9	20	2.4%	4.6%	6.7	4.7
179	Jim Hart	1966--1984	crd-was	35156	93	5.7%	4%	7.6	5.9	103	2.9%	5.5%	6.2	3.8
180	Vince Young	2006--2011	oti-phi	9102	35	4.5%	3%	7.1	5.9	27	2.2%	4.9%	6.5	4.3
181	Josh McCown	2002--2011	crd-det-rai-car-chi	6998	15	4.2%	1.6%	6.5	5.9	36	2.9%	5.2%	6.2	3.9
182	Mark Malone	1981--1989	pit-sdg-nyj	10733	29	6.3%	3%	7.1	5.8	44	2.3%	5.9%	5.8	3.2
183	Babe Parilli	1960--1969	rai-nwe-nyj	18778	64	7.1%	4.1%	7.5	5.8	47	3.2%	7.5%	5.9	2.5
184	Don Strock	1974--1988	mia-cle	5913	37	7.1%	3.6%	7.3	5.8	30	4.5%	7.3%	6.6	3.3
185	Dick Wood	1962--1966	sdg-nyj-rai-mia	7153	17	7.1%	3.4%	7.2	5.8	28	2.6%	7.3%	5.3	2.1
186	Shaun King	1999--2004	tam-crd	5057	19	5.9%	2.3%	6.7	5.8	16	1.1%	4.1%	5.5	3.7
187	Pat Haden	1976--1981	ram	10024	41	4.4%	2.9%	7	5.8	26	3.1%	7.1%	6.4	3.3
188	Bobby Douglass	1969--1978	chi-sdg-nor-gnb	6493	16	6.2%	3.5%	7.2	5.8	57	2.1%	5.8%	5.1	2.5
189	Cotton Davidson	1960--1968	kan-rai	11451	30	6.5%	4.1%	7.5	5.7	40	2.9%	7.2%	6.3	3.1
190	Steve Bono	1985--1999	min-pit-sfo-kan-gnb-ram-car	10576	49	4.6%	1.8%	6.4	5.7	26	2.5%	3.7%	5.7	4.1
191	Marc Wilson	1980--1990	rai-nwe	14526	39	5.8%	4%	7.4	5.7	42	2.8%	5.8%	6.5	3.9
192	Billy Joe Tolliver	1989--1999	sdg-atl-oti-kan-nor	10760	24	5%	2.6%	6.8	5.7	53	3%	4.1%	6.1	4.4
193	Rick Mirer	1993--2003	sea-chi-nyj-sfo-rai	11969	27	3.9%	2.4%	6.6	5.6	52	1.8%	4.4%	5.5	3.5
194	Steve Ramsey	1970--1976	nor-den	6437	23	5.4%	5.9%	8.1	5.6	28	2.4%	6.5%	6.3	3.4
195	Jacky Lee	1960--1969	oti-den-kan	6191	30	9%	7%	8.5	5.5	29	4%	6.9%	6.6	3.6
196	Hugh Millen	1987--1995	ram-atl-nwe-den	6440	8	2.3%	4.2%	7.4	5.5	30	2.4%	3.6%	6.8	5.2
197	Jim Ninowski	1960--1969	det-cle-was-nor	6953	33	4.3%	4.5%	7.5	5.5	27	2.6%	7.4%	6.2	2.9
198	Dave Wilson	1981--1988	nor	7007	16	4.2%	5.2%	7.8	5.5	37	3.1%	5.5%	6.2	3.8
199	Kyle Boller	2003--2011	rav-ram-rai	8931	30	4.1%	1.7%	6.2	5.5	36	2.6%	4.7%	5.7	3.6
200	Joey Harrington	2002--2007	det-mia-atl	14693	27	4.4%	2.2%	6.4	5.5	55	2.5%	3.8%	5.5	3.9
201	Todd Blackledge	1983--1989	kan-pit	5366	22	5.2%	3.4%	6.9	5.5	22	1.7%	5.2%	5.3	2.9
202	Mike Tomczak	1985--1999	chi-gnb-cle-pit	16963	79	3.8%	3.9%	7.1	5.5	59	3.4%	5.3%	6.6	4.2
203	Mike Livingston	1968--1979	kan	11295	37	4.4%	3.2%	6.8	5.5	52	2.4%	5.7%	6.2	3.7
204	Danny Kanell	1996--2003	nyg-atl-den	5328	14	5.3%	2.5%	6.5	5.5	25	2.2%	4%	4.9	3.2
205	Steve Dils	1980--1988	min-ram-atl	5816	18	3.5%	2.6%	6.5	5.4	29	2.4%	3.6%	5.7	4.1
206	Jack Thompson	1979--1984	cin-tam	5329	15	5.3%	1.8%	6.1	5.4	30	3.5%	6.2%	6.3	3.6
207	Kent Graham	1992--2001	nyg-crd-pit-was	7801	27	4.4%	1.6%	6	5.4	33	1.8%	3.1%	5.7	4.3
208	David Woodley	1980--1985	mia-pit	9203	38	4.4%	3.5%	6.9	5.4	24	3%	7.4%	6.3	3.1
209	Randy Johnson	1966--1976	atl-nyg-was-gnb	8329	14	7.8%	4.4%	7.2	5.4	58	3.2%	7.6%	6.3	3
210	Rex Grossman	2003--2011	chi-htx-was	11015	30	4.7%	3.3%	6.8	5.4	27	2.3%	4.3%	6.2	4.3
211	Jim Miller	1995--2002	pit-chi	6410	20	3.9%	2.9%	6.6	5.3	18	3%	3.2%	5.6	4.3
212	Dan Pastorini	1971--1983	oti-rai-ram-phi	19469	62	4.6%	4.2%	7.1	5.3	81	2.5%	6.1%	5.4	2.7
213	Paul McDonald	1980--1984	cle	5550	12	3.8%	3.4%	6.8	5.3	23	2.8%	5.1%	7	4.7
214	George Blanda	1960--1975	oti-rai	22029	142	8.4%	6%	7.8	5.3	79	3.9%	8%	6.1	2.5
215	Jack Kemp	1960--1969	sdg-buf	22256	71	4.6%	5.2%	7.5	5.2	46	2.2%	7.1%	6.2	3
216	David Whitehurst	1977--1983	gnb	6205	21	6.1%	5.3%	7.4	5.1	30	1.1%	5.4%	5.7	3.3
217	Zeke Bratkowski	1960--1971	chi-ram-gnb	8005	30	4.7%	5.5%	7.5	5.1	45	3.5%	8.9%	6.6	2.7
218	Steve Spurrier	1967--1976	sfo-tam	6878	48	6.4%	4.9%	7.1	5.1	53	2.2%	5.2%	5.4	3.1
219	Joe Kapp	1967--1970	min-nwe	6746	26	6.6%	6.2%	7.7	5.1	26	2.2%	8.1%	5.7	2.1
220	Bob Avellini	1975--1984	chi	7288	30	4.2%	5.9%	7.5	5	36	2.3%	6.8%	5.7	2.7
221	Frank Tripucka	1960--1963	den	7676	13	5.1%	5.9%	7.5	5	29	3.3%	6.7%	5.2	2.3
222	Pete Beathard	1964--1973	kan-oti-crd-ram	8544	40	4.5%	5.3%	7.2	4.9	34	2.5%	7.3%	5.6	2.4
223	Gary Cuozzo	1963--1972	clt-nor-min-crd	7688	47	4.6%	3.9%	6.5	4.9	35	2.9%	5.7%	6	3.5
224	Al Dorow	1960--1962	nyj-buf	5732	14	5.7%	5%	6.9	4.8	18	4.7%	8.5%	5.8	2.1
225	Steve Walsh	1989--1999	dal-nor-chi-ram-tam-clt	8248	27	3.9%	3.2%	6.2	4.8	34	2.4%	4.5%	5.9	3.9
226	Mike Phipps	1970--1981	cle-chi	10806	50	4.5%	3.7%	6.4	4.8	51	1.7%	8.4%	5.3	1.6
227	Scott Brunner	1980--1985	nyg-crd	6843	16	3.7%	3.7%	6.3	4.7	29	3%	5.8%	6.2	3.6
228	Jack Concannon	1964--1975	phi-chi-gnb-det	6270	27	4.6%	4.3%	6.5	4.6	32	2.5%	6.8%	5.1	2.1
229	Mike Taliaferro	1964--1972	nyj-nwe-buf	5241	19	8.2%	4.7%	6.3	4.4	41	2.2%	7.2%	5.1	1.9

[continue reading…]

References[+]

References
↑1	Unfortunately, I excluded sack data from this study due to its general unavailability for most of the covered time period.

Tagged as: Aaron Rodgers, Dan Marino, Joe Montana, Peyton Manning, quarterbacks, Tom Brady

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Checkdowns: Adjusted Net Yards per Attempt “FIP” for Quarterbacks

by Neil Paine on December 22, 2012

in Checkdowns, Passing, Quarterbacks, Statgeekery, Totally Useless

I’ve been on a major QB kick lately, and there’s no reason to stop now. Today, I want to look at a method that might tease out a quarterback’s “true talent” better than if we simply use his raw stats from the season.

Three years ago, our colleague Jason Lisk had a post on the old PFR Blog about which rate stats stay consistent when a QB changes teams. Basically, he grabbed QBs who were still in their primes and changed teams, looking at how their key rate stats correlated from one year to the next. Here’s what Jason found:

[…]I looked at the correlation coefficient for our group of 48 passers, for the year N advanced passing score compared to the year N+1 advanced passing score in each category. This should tell us whether the passers who were good in a performance area (or bad) tended to be the ones who remained good in that performance area the following season, even with the uncertainty of team changes (some positive, some negative for the quarterback).
Sack Percentage:  0.31
Completion Percentage: 0.25
Yards Per Attempt:  0.20
Touchdown Percentage: 0.12
Interception Percentage: 0.10

What do those correlations mean, exactly? Well, take sack percentage as an example. In general, a correlation of 0.31 means you can expect 31% of a QB’s difference from the mean to be repeated next year when he changes teams. In other words, you have to regress the QB’s sack rate 69% towards the mean to get the true rate that “belongs” to him. If the average sack rate is 6.1%, and a QB has a rate of 4.0% (like, say, Drew Brees this year), his “true” sack rate is probably something like 5.4% — 31% of the distance between .061 and .040.

The same concept applies to the other stats listed above. Tony Romo’s observed 66.7% completion percentage is really more like 62.5% after regressing to the mean, and so forth. Do that for every QB who had a reasonable number of attempts this year, and you get these rate stats:

Player	Tm	G	GS	Att	A-Sk%	A-Cmp%	A-YPA	A-TD%	A-INT%	R-Sk%	R-Cmp%	R-YPA	R-TD%	R-INT%
Matthew Stafford	DET	14	14	629	4.3	59.5	6.8	2.7	2.4	5.5	60.7	7.0	4.0	2.6
Drew Brees	NOR	14	14	574	4.0	62.0	7.6	6.3	3.1	5.4	61.4	7.2	4.5	2.7
Tony Romo	DAL	14	14	568	5.3	66.7	7.5	3.9	2.8	5.9	62.5	7.2	4.2	2.7
Andrew Luck	IND	14	13	564	6.2	54.6	7.1	3.5	3.2	6.1	59.5	7.1	4.1	2.7
Carson Palmer	OAK	14	14	562	4.4	60.9	7.1	3.9	2.5	5.6	61.1	7.1	4.2	2.6
Tom Brady	NWE	14	14	560	3.9	63.4	7.6	5.4	1.1	5.4	61.7	7.2	4.4	2.5
Matt Ryan	ATL	14	14	539	4.4	68.5	7.8	5.0	2.6	5.6	63.0	7.2	4.3	2.7
Peyton Manning	DEN	14	14	511	3.9	67.9	7.9	6.1	2.0	5.4	62.8	7.2	4.4	2.6
Brandon Weeden	CLE	14	14	498	5.0	57.2	6.6	2.8	3.4	5.7	60.2	7.0	4.0	2.7
Philip Rivers	SDG	14	14	488	8.1	64.3	6.7	4.5	3.1	6.7	62.0	7.0	4.2	2.7
Joe Flacco	BAL	14	14	487	6.5	59.1	7.1	4.1	2.1	6.2	60.7	7.1	4.2	2.6
Eli Manning	NYG	14	14	487	3.0	60.4	7.4	4.1	3.1	5.1	61.0	7.1	4.2	2.7
Sam Bradford	STL	14	14	482	6.8	60.2	6.8	3.7	2.3	6.3	60.9	7.0	4.2	2.6
Matt Schaub	HOU	14	13	476	4.0	64.7	7.5	4.6	2.1	5.5	62.0	7.2	4.3	2.6
Aaron Rodgers	GNB	14	14	474	8.7	66.7	7.6	6.8	1.7	6.9	62.5	7.2	4.5	2.6
Andy Dalton	CIN	14	14	472	7.5	62.5	7.0	5.5	3.0	6.5	61.5	7.1	4.4	2.7
Josh Freeman	TAM	14	14	469	4.3	54.8	7.4	5.3	2.6	5.5	59.6	7.1	4.3	2.7
Ryan Fitzpatrick	BUF	14	13	444	5.9	61.7	6.6	5.0	3.4	6.0	61.3	7.0	4.3	2.7
Christian Ponder	MIN	14	14	425	6.6	63.1	5.9	3.3	2.8	6.2	61.6	6.9	4.1	2.7
Ryan Tannehill	MIA	14	14	424	5.8	58.7	6.9	2.4	2.8	6.0	60.5	7.0	4.0	2.7
Cam Newton	CAR	14	14	423	7.2	58.2	8.2	4.3	2.4	6.4	60.4	7.3	4.2	2.6
Mark Sanchez	NYJ	14	14	418	7.3	54.8	6.4	3.1	4.1	6.5	59.6	6.9	4.1	2.8
Ben Roethlisberger	PIT	11	11	398	5.7	64.1	7.3	5.5	1.5	6.0	61.9	7.1	4.4	2.6
Jay Cutler	CHI	13	13	377	8.5	59.7	7.0	4.5	3.7	6.8	60.8	7.1	4.2	2.8
Russell Wilson	SEA	14	14	353	6.9	62.9	7.6	5.9	2.5	6.3	61.6	7.2	4.4	2.7
Robert Griffin III	WAS	13	13	351	7.4	66.4	8.3	5.1	1.1	6.5	62.5	7.3	4.3	2.5
Michael Vick	PHI	9	9	316	7.9	58.5	6.9	3.5	2.8	6.6	60.5	7.0	4.1	2.7
Blaine Gabbert	JAX	10	10	278	7.3	58.3	6.0	3.2	2.2	6.5	60.4	6.9	4.1	2.6
Matt Cassel	KAN	9	8	277	6.4	58.1	6.5	2.2	4.3	6.2	60.4	7.0	4.0	2.8
Jake Locker	TEN	9	9	269	5.6	57.6	7.0	3.3	3.3	5.9	60.3	7.1	4.1	2.7
Matt Hasselbeck	TEN	8	5	221	6.0	62.4	6.2	3.2	2.3	6.1	61.5	6.9	4.1	2.6
Nick Foles	PHI	6	5	217	6.5	59.4	6.2	2.3	1.8	6.2	60.7	6.9	4.0	2.6
Alex Smith	SFO	9	9	217	10.0	70.0	8.0	6.0	2.3	7.3	63.4	7.3	4.4	2.6
Chad Henne	JAX	8	4	216	8.5	51.9	6.7	3.7	2.3	6.8	58.8	7.0	4.2	2.6
John Skelton	ARI	7	6	201	6.9	54.2	5.6	1.0	4.5	6.4	59.4	6.8	3.8	2.8
Kevin Kolb	ARI	6	5	183	12.9	59.6	6.4	4.4	1.6	8.2	60.8	6.9	4.2	2.6
Brady Quinn	KAN	8	6	159	9.1	59.7	5.8	1.3	3.8	7.0	60.8	6.8	3.9	2.8
Colin Kaepernick	SFO	11	5	154	8.3	65.6	8.4	4.5	1.3	6.8	62.3	7.3	4.3	2.5
Ryan Lindley	ARI	6	3	141	6.6	51.1	4.3	0.0	4.3	6.3	58.6	6.5	3.7	2.8

(“A-” before a stat means the actual observed rate; “R-” means the regressed rate.)

Now we just need to reconstruct the player’s raw passing line as though he posted those rate stats instead of his actual rates. Cmp%, YPA, TD%, and INT% are easy (just multiply by attempts), and Sack% can be derived via simple algebra:

Sacks_new = (-reg_sk% * Attempts) / (reg_sk% – 1)

(Sack yards can be assumed by multiplying raw sack yards per sack by the new sack total.)

Finally, we plug the new totals into the Adjusted Net Yards Per Attempt formula, and we have a QB stat that is sort of like baseball’s Fielding Independent Pitching (FIP), which also seeks to reduce the noise and teammate interactions in a pitcher’s ERA by reducing his performance to only those elements he has control over — strikeouts, walks, and home runs.

Here are the 2012 leaders in QB-FIP (along with their regressed totals):

Rk	Player	Age	Tm	G	GS	Cmp	Att	Yds	TD	Int	Sk	SkYds	QB-FIP
1	Peyton Manning	36	DEN	14	14	321	511	3697	23	13	29	191	6.22
2	Tom Brady	35	NWE	14	14	346	560	4027	24	14	32	214	6.20
3	Robert Griffin III	22	WAS	13	13	219	351	2568	15	9	24	166	6.15
4	Colin Kaepernick	25	SFO	11	5	96	154	1130	7	4	11	76	6.11
5	Ben Roethlisberger	30	PIT	11	11	246	398	2836	17	10	25	141	6.11
6	Matt Ryan	27	ATL	14	14	339	539	3893	23	14	32	225	6.11
7	Eli Manning	31	NYG	14	14	297	487	3476	20	13	26	165	6.09
8	Drew Brees	33	NOR	14	14	352	574	4118	26	16	33	237	6.08
9	Josh Freeman	24	TAM	14	14	279	469	3350	20	12	27	181	6.08
10	Aaron Rodgers	29	GNB	14	14	296	474	3402	21	12	35	197	6.06
11	Cam Newton	23	CAR	14	14	256	423	3086	18	11	29	203	6.05
12	Russell Wilson	24	SEA	14	14	217	353	2539	16	9	24	148	6.05
13	Alex Smith	28	SFO	9	9	138	217	1575	10	6	17	97	6.04
14	Matt Schaub	31	HOU	14	13	295	476	3407	20	12	27	228	6.01
15	Tony Romo	32	DAL	14	14	355	568	4071	24	15	35	255	5.97
16	Andy Dalton	25	CIN	14	14	290	472	3336	21	13	33	176	5.94
17	Joe Flacco	27	BAL	14	14	295	487	3453	20	13	32	209	5.93
18	Carson Palmer	33	OAK	14	14	343	562	3980	23	15	33	254	5.92
19	Ryan Fitzpatrick	30	BUF	14	13	272	444	3101	19	12	29	151	5.89
20	Andrew Luck	23	IND	14	13	336	564	3990	23	15	37	230	5.89
21	Matthew Stafford	24	DET	14	14	382	629	4413	25	17	37	256	5.88
22	Jake Locker	24	TEN	9	9	162	269	1900	11	7	17	108	5.88
23	Michael Vick	32	PHI	9	9	191	316	2223	13	8	22	124	5.84
24	Sam Bradford	25	STL	14	14	294	482	3380	20	13	32	216	5.82
25	Brandon Weeden	29	CLE	14	14	300	498	3477	20	14	30	198	5.80
26	Ryan Tannehill	24	MIA	14	14	257	424	2987	17	11	27	205	5.78
27	Chad Henne	27	JAX	8	4	127	216	1511	9	6	16	94	5.78
28	Philip Rivers	31	SDG	14	14	302	488	3422	21	13	35	221	5.77
29	Matt Cassel	30	KAN	9	8	167	277	1928	11	8	18	97	5.75
30	Jay Cutler	29	CHI	13	13	229	377	2661	16	10	28	187	5.74
31	Christian Ponder	24	MIN	14	14	262	425	2912	17	11	28	164	5.70
32	Nick Foles	23	PHI	6	5	132	217	1500	9	6	14	102	5.70
33	Matt Hasselbeck	37	TEN	8	5	136	221	1525	9	6	14	105	5.70
34	Mark Sanchez	26	NYJ	14	14	249	418	2903	17	12	29	178	5.68
35	Blaine Gabbert	23	JAX	10	10	168	278	1907	11	7	19	138	5.61
36	Kevin Kolb	28	ARI	6	5	111	183	1270	8	5	16	96	5.61
37	Brady Quinn	28	KAN	8	6	97	159	1086	6	4	12	70	5.50
38	John Skelton	24	ARI	7	6	119	201	1365	8	6	14	89	5.46
39	Ryan Lindley	23	ARI	6	3	83	141	921	5	4	9	72	5.15
	Lg Average												5.92

{ 3 comments }

Checkdowns: Quarterback Yards Above Bench (QBYAB)

by Neil Paine on December 21, 2012

in Checkdowns, Passing, Quarterbacks, Statgeekery, Totally Useless

These guys are pretty good.

After posting about SRS-style quarterback ratings on Monday, I was thinking about other things we can do with game-by-game data like that. In his QBGOAT series, Chase likes to compare QBs to the league average, which makes a lot of sense for all-time ratings — you want to reward guys who are at least above-average in a ranking like that. However, if we want seasonal value, perhaps average is too high a baseline.

Over at Football Outsiders, Aaron Schatz has always compared to “replacement level”, borrowing a concept from baseball. I like that approach, but replacement level can be hard to empirically determine. So for the purposes of this post, I wanted to come up with a quick-and-dirty baseline to which we can compare QBs.

To that end, I looked at all players who were not their team’s primary passer in each game since 2010. Weighted by recency and the number of dropbacks by each passer, they performed at roughly a 4.4 Adjusted Net Yards Per Attempt level. This is not necessarily the replacement level, but it does seem to be the “bench level” — i.e., the ANYPA you could expect from a backup-caliber QB across the league.

Using 4.4 ANYPA as the baseline, we get the following values for 2012:

Quarterback	QBYAB
Tom Brady	1888.1
Peyton Manning	1708.2
Matt Ryan	1453.4
Drew Brees	1441.8
Aaron Rodgers	1337.4
Robert Griffin III	1226.6
Matt Schaub	1205.1
Josh Freeman	1140.1
Cam Newton	1128.2
Tony Romo	1120.2
Ben Roethlisberger	1082.8
Carson Palmer	1011.9
Eli Manning	1002.9
Joe Flacco	914.8
Russell Wilson	890.5
Matthew Stafford	834.1
Andy Dalton	756.9
Andrew Luck	691.6
Sam Bradford	616.3
Alex Smith	558.5
Colin Kaepernick	506.5
Ryan Fitzpatrick	481.1
Philip Rivers	447.7
Ryan Tannehill	409.6
Brandon Weeden	320.4
Michael Vick	317.5
Jake Locker	316.9
Jay Cutler	293.8
Chad Henne	217.4
Kirk Cousins	156.8
Nick Foles	152.5
Shaun Hill	151.9
Matt Hasselbeck	134.0
Kevin Kolb	121.4
Blaine Gabbert	92.2
Christian Ponder	91.0
Mohamed Sanu	87.7
Kyle Orton	62.8
Matt Moore	52.5
Derek Anderson	30.1
Matt Flynn	23.7
Dan Orlovsky	17.6
Greg McElroy	11.4
Tyrod Taylor	9.2
Rusty Smith	9.1
Chase Daniel	5.6
Tyler Thigpen	2.7
Graham Harrell	-1.6
Terrelle Pryor	-4.4
Matt Leinart	-5.1
David Carr	-5.9
Tim Tebow	-6.3
Mark Sanchez	-13.3
Charlie Batch	-17.8
Kellen Clemens	-22.4
Ryan Mallett	-45.9
Byron Leftwich	-46.6
Matt Cassel	-47.7
Brad Smith	-50.0
T.J. Yates	-55.1
Jason Campbell	-88.4
Brady Quinn	-146.4
John Skelton	-309.2
Ryan Lindley	-382.0

If we weigh each game by how recent the results took place, we get this list:

Quarterback	Wgtd QBYAB
Tom Brady	1527.6
Drew Brees	1205.4
Peyton Manning	1202.0
Matt Ryan	1129.8
Aaron Rodgers	1109.4
Tony Romo	961.1
Cam Newton	936.6
Matt Schaub	900.3
Robert Griffin III	869.5
Eli Manning	795.5
Ben Roethlisberger	793.9
Josh Freeman	790.3
Carson Palmer	760.4
Russell Wilson	722.9
Matthew Stafford	687.5
Joe Flacco	666.3
Andy Dalton	520.4
Andrew Luck	479.9
Sam Bradford	459.9
Colin Kaepernick	443.0
Alex Smith	399.3
Philip Rivers	384.9
Ryan Fitzpatrick	324.0
Ryan Tannehill	313.1
Brandon Weeden	266.5
Michael Vick	249.9
Jay Cutler	236.8
Jake Locker	192.4
Chad Henne	178.7
Kirk Cousins	158.7
Nick Foles	150.5
Matt Hasselbeck	133.1
Shaun Hill	84.4
Kevin Kolb	70.6
Matt Moore	64.8
Kyle Orton	59.8
Mohamed Sanu	47.4
Matt Flynn	47.4
Blaine Gabbert	39.9
Dan Orlovsky	26.3
Tim Tebow	16.3
Derek Anderson	16.3
Greg McElroy	10.3
Chase Daniel	5.1
Rusty Smith	4.8
Tyrod Taylor	4.0
Tyler Thigpen	-0.8
Graham Harrell	-1.4
Matt Leinart	-2.8
David Carr	-3.3
Terrelle Pryor	-4.4
Charlie Batch	-7.6
Kellen Clemens	-14.0
Matt Cassel	-24.2
T.J. Yates	-29.7
Brad Smith	-33.2
Byron Leftwich	-38.3
Christian Ponder	-39.4
Ryan Mallett	-44.6
Jason Campbell	-51.1
Mark Sanchez	-91.0
Brady Quinn	-113.4
John Skelton	-263.6
Ryan Lindley	-340.5

This kind of thing isn’t exactly the most advanced stat in the world, but it’s pretty good if you want to sort QBs into general groups based on how good they are (the assumption being that a player who never plays is implicitly a bench-level player by definition).

Tagged as: Peyton Manning, Tom Brady

{ 2 comments }

Every hand in the Jets passing game is to blame

by Chase Stuart on December 8, 2012

in Passing, Rant

Not Don Coryell.

It’s a special edition of Saturday rant day at Football Perspective.

I’m no Mark Sanchez apologist. But that doesn’t mean he’s the only one to blame for the Jets’ passing game struggles.

The Supporting Cast
Jeremy Kerley, Dustin Keller, Chaz Schilens, Stephen Hill, and Jeff Cumberland are the team’s leading receivers. Clyde Gates has started two games at wide receiver. Kerley would be a great #3 receiver, but he’s the Jets #1. Schillens and Gates are best left as fifth receivers, while Stephen Hill is incredibly raw and has struggled most of the year. Keller would be a good tight end on a good passing offense, but is overmatched as the team’s #2 target. I don’t think anyone would disagree that the Jets’ receivers (including stone-hands Shonn Greene) rank in the bottom five of the league.

Mike Tannenbaum

Tannenbaum has come under heavy criticism from Jets fans of late. While I think much of that is probably unfair, there are several areas to point the finger at Tannenbaum — starting with drafting Sanchez in the first place. The Jets general manager listens to eternal optimist Ryan too much when it comes to personnel decisions, which led the Jets to start Wayne Hunter at right tackle last year and enter the pre-season with him, somehow, still entrenched at the spot. The Vlad Ducasse pick has been a bust, leaving Matt Slauson to cover at left guard (you know, when he’s not being rotated out of the game). Trades for Braylon Edwards and Santonio Holmes yielded immediate dividends, but have only added to the disruption in the locker room without helping the 2012 version of the team. Sanchez is playing with one of the worst supporting casts in the league, so the man who picks the talent certainly bears some of the blame.

Rex Ryan

There are very few head coaches who are excellent on both sides of the ball, but Rex Ryan is one of the most specialized head coaches in the NFL. He’s a defensive mastermind — no doubt about that — but he’s as helpless on offense as he is strong on defense. He vowed this year to get more involved in the offense, which should start sending red flags to begin with since 2012 is his fourth season as head coach of the team. To the extent that he has been more hands on in 2012, the results aren’t any better.

Perhaps Ryan is the mirror image of a Gary Kubiak, who took awhile to find the right man to run the other half of his team. But from the standpoint of developing a quarterback, Ryan may even be counterproductive. The red light-yellow light-green light system he gave Sanchez in his rookie season was Ryan’s first attempt to right the ship and a sign of what the coach expects out of the quarterback position. The bottom line is Ryan is focused on playing good defense and running the ball, and as long as his quarterback doesn’t mess up, he thinks his team will win. That’s not the ideal environment for a young quarterback to blossom in, and we learned exactly what Rex thinks about his quarterback when this off-season he chose to hire as his offensive coordinator…

Tony Sparano (hat tip, Brian Schottenheimer)
[continue reading…]

Tagged as: Jets, Mark Sanchez, Rex Ryan, Tony Sparano

{ 3 comments }

The 2013 Panthers are so attractive Bill Parcells could be lured out of retirement

by Chase Stuart on December 7, 2012

in Coaches, Passing, Quarterbacks

So you're telling me they were 1-15 last year?

An old friend of mine was always mildly irked at the praise thrown at Bill Parcells for turning around moribund franchises. In reality, making a team with a terrible record respectable isn’t all that challenging. Where Parcells added value was in making his good teams great, not in making terrible teams mediocre.

In 1992, one year B.P., the New England Patriots were 2-14, in part thanks to a 1-5 record in one-score games. Throw in some regression to the mean and the first pick in every round of the ’93 draft, and going 5-11 in 1993 wasn’t so much of an accomplishment as it was pre-ordained.

In 1996, one year B.P., the Jets went 1-15. New York was a horrific 0-7 in one-score games. Throw in the #1 pick in every round, and they were an attractive target. Parcells did do a masterful job cleaning up the mess left by Rich Kotite, but getting them to 9-7 looked very impressive in large part thanks to the poor fortunes of the team the prior year.

The Big Tuna again went after the low-hanging fruit again when he took over as the Executive Vice President of Football Operations in Miami (it is here my old friend would get particularly annoyed, noting that Parcells found a way to have his cake and eat it too. If the Dolphins succeeded, Parcells would have “done it again.” Had they failed, well, he wasn’t the coach.) He took over a 1-15 team that was bad but not 1-15 bad; they had faced one of the harder schedules in the league and gone 1-6 in close games. Enter Jake Long, Chad Pennington, and the Wildcat, and the Dolphins went 11-5. Parcells did it again!

In any event, that’s just background. The 2013 Panthers are the real topic today — and they are the lowest hanging fruit any potential coach has seen in decades. Consider:

The Panthers are currently 3-9, and little is expected of them going forward. They are now just 9-19 in the Cam Newton era.
Despite that, Carolina ranks 4th in Brian Burke’s Advanced NFL Stats efficiency ratings. Now maybe they aren’t the 4th best team in the league, but Brian’s system is purely predictive and minimizes events that shape our views but are unlikely to impact future records. I have no doubt that they’re closer to the 4th best team in the league than the 4th worst, which is where they are by record.
Football Outsiders ranks Carolina 18th — which, by the way, still means they’re much better than their record — but even that is misleading. Schatz ranks Carolina 32nd in special teams — a unit that Burke ignores — but instead has them 15th in offensive DVOA and 14th in defensive DVOA. That means excluding special teams the Panthers are above average, and special teams performance is notoriously fickle.
So why are the Panthers 3-9? Carolina is currently 0-7 in one-score games.

There’s an even simpler way to show how the Panthers are massively underachieving this year. Net yards per attempt isn’t the only stat in the world, but it’s one of the most important indicators of an offense’s effectiveness. Net yards per attempt is just as important on defense; NY/A differential, the difference between how many net yards you gain per offensive attempt and how many you allow per defensive attempt, is a simple shorthand to highlight the best in the league. Here are the results through 13 weeks (i.e., not counting last night’s game):
[continue reading…]

Tagged as: Cam Newton, Jon Gruden, Panthers, Ron Rivera

{ 11 comments }

Checkdowns: Greg McElroy gets a 4QC/GWD in his first game

by Chase Stuart on December 3, 2012

in Checkdowns, Passing

Scott Kacsmar has been keeping track of 4th quarter comebacks and game-winning drives for some time. As a technical matter, Greg McElroy earned both a 4th quarter comeback and led a game-winning drive in his first game ever yesterday. How rare is that?

The table below shows all the quarterbacks to lead 4th quarter comebacks and game-winning drives. Some of these, like Brian St. Pierre’s “comeback win” — and to a large extent, McElroy’s 4QC/GWD — are far from laudable. Still, here is the list:

Year	Name	Tm	Opp	Week	Final Score
2012	Greg McElroy	NYJ	ARI	13	7-6
2005	Ryan Fitzpatrick	STL	HOU	12	33-27
2004	Brian St. Pierre	PIT	BUF	17	29-24
2001	A.J. Feeley	PHI	TAM	17	17-13
1998	Ryan Leaf	SDG	BUF	1	16-14
1997	Jim Druckenmiller	SFO	STL	2	15-12
1987	Mike Kelley	SDG	CIN	3	10-9
1987	Brian McClure	BUF	NYG	5	6-3
1985	Dieter Brock	RAM	DEN	1	20-16
1985	Bernie Kosar	CLE	NWE	5	24-20
1985	Steve Young	TAM	DET	12	19-16
1981	Turk Schonert	CIN	SEA	1	27-21
1977	Jerry Golsteyn	NYG	WAS	1	20-17
1974	Clint Longley	DAL	WAS	12	24-23
1971	Archie Manning	NOR	RAM	1	24-20
1961	Sam Etcheverry	STL	NYG	1	21-10
1961	Warren Rabb	BUF	HOU	5	22-12
1960	Bob Waters	SFO	BAL	9	30-22

{ 1 comment }

Ranking NFL quarterbacks by how much ‘it’ they have

by Chase Stuart on November 9, 2012

in Passing, Rant

Yep, that's it.

2) Tom Brady, New England Patriots. Until further notice, nobody has more ‘it’ than Tom Brady, who has been overflowing with ‘it’ since his first year as a starter. He’s the only active quarterback with three Super Bowl rings. However, since he has lost two Super Bowls to Eli Manning, I guess Manning has more “it.” So…

1) Eli Manning, New York Giants. If to be the man you have to beat the man, well, Eli Manning is now the man. Nobody has ‘it’ in the 4th quarter quite like Eli, which is when ‘it’ becomes really important.

3) Peyton Manning, Denver Broncos. If ‘it’ was Tapenade, Manning would be first on the list.

4) Ben Roethlisberger, Pittsburgh Steelers. With two Super Bowl rings, Roethlisberger arguably has more ‘it’ than Manning, but to be fair, Peyton Manning does hold the record for the most 4th quarter comebacks.

5) Drew Brees, New Orleans Saints. Despite gaudy numbers, Brees kind of doesn’t have that much ‘it’, in my opinion. But I’m not sure who else could go ahead of him.

6) Aaron Rodgers, Green Bay Packers. The last of the quarterbacks with rings, as Rodgers has one of the worst records in history when it comes to 4th quarter comebacks.

7) Tim Tebow, New York Jets. Without question, in possession of more ‘it’ than any quarterback without a Super Bowl ring, and maybe even more than some of the ones who do.

8) Alex Smith, San Francisco 49ers. This dude is loaded with ‘it’ and grit and teammates that hit. He went about 20 games without throwing an interception and he nearly completed more than 100% of his passes a couple of weeks ago.

9) Joe Flacco, Baltimore Ravens. If ‘it’ is Ray Lewis, Haloti Ngata, Ray Rice, Lardarius Webb, and Ed Reed, then Joe Flacco has had ‘it’ in spades for years. Let’s not forget he outplayed Mr. It in the AFC Championship Game last year, a particularly notable feat since both quarterbacks were playing against identical defenses.

10) Robert Griffin III, Washington Redskins. It doesn’t matter that his team loses, he has ‘it’ until the first game he struggles in 2013.
[continue reading…]

{ 8 comments }

Quarterback performance on third and fourth downs

by Chase Stuart on November 7, 2012

in Passing, Statistics

So far this season, teams have converted on 37.2% of all pass plays on third or fourth downs. Looking at success rates on these downs helps to identify which quarterbacks are keeping drives alive for their teams and coming through in the most important situations. For example, Peyton Manning leads the league with an impressive 52.6% rate. How impressive is that?

The table below lists the conversion rates for quarterbacks on passing plays (excluding scrambles) on third and fourth downs; the table is sorted by the far right column, which shows how many third downs over average each quarterback converted. This is calculated by subtracting from the number of actual conversions the number of expected conversions (which is 37.2% multiplied by the number of third down plays):

Rank	Quarterback	Plays	Conv	Rate	3DCovOvAvg
1	Peyton Manning	78	41	52.6%	12
2	Ben Roethlisberger	97	46	47.4%	9.9
3	Matt Ryan	79	39	49.4%	9.6
4	Drew Brees	104	47	45.2%	8.3
5	Andrew Luck	99	44	44.4%	7.1
6	Matthew Stafford	102	45	44.1%	7
7	Tom Brady	86	38	44.2%	6
8	Matt Schaub	72	32	44.4%	5.2
9	Matt Hasselbeck	78	34	43.6%	5
10	Matt Cassel	71	31	43.7%	4.6
11	Ryan Fitzpatrick	80	34	42.5%	4.2
12	Tony Romo	91	38	41.8%	4.1
13	Michael Vick	95	39	41.1%	3.6
14	Aaron Rodgers	94	37	39.4%	2
15	Jay Cutler	84	33	39.3%	1.7
16	Christian Ponder	94	35	37.2%	0
17	Philip Rivers	84	30	35.7%	-1.3
18	Ryan Tannehill	78	27	34.6%	-2
19	Eli Manning	89	31	34.8%	-2.1
20	Alex Smith	61	20	32.8%	-2.7
21	Josh Freeman	80	27	33.8%	-2.8
22	Kevin Kolb	68	22	32.4%	-3.3
23	Sam Bradford	87	29	33.3%	-3.4
24	Mark Sanchez	96	32	33.3%	-3.7
25	Russell Wilson	83	27	32.5%	-3.9
26	Brandon Weeden	111	37	33.3%	-4.3
27	John Skelton	59	16	27.1%	-6
28	Robert Griffin III	78	23	29.5%	-6
29	Carson Palmer	92	28	30.4%	-6.3
30	Cam Newton	68	19	27.9%	-6.3
31	Joe Flacco	78	21	26.9%	-8
32	Blaine Gabbert	84	22	26.2%	-9.3
33	Andy Dalton	77	16	20.8%	-12.7

[continue reading…]

{ 3 comments }

How much does Philip Rivers’ decline have to do with Philip Rivers?

by Chase Stuart on October 29, 2012

in Passing, Statistics

For years, I was an unabashed Philip Rivers supporter. I had no preexisting affinity for the Chargers or Rivers, but in all the metrics I care about, Rivers was always one of the best. In 2008, 2009, and 2010, Philip Rivers led the league in yards per attempt. He finished first in ANY/A in ’08 and second in ’09 and ’10; he finished second in NY/A in ’08 and then first in NY/A in 2009 and 2010. Simply put, going into the 2011 season, no quarterback had been better over the last three years.

Rank	Player	Tm	Gms	Cmp	Att	Cmp%	Yds	TD	Int	Rate	Sk	Y/A	SkYds	AY/A	ANY/A	Y/G
1	Philip Rivers	SDG	48	986	1505	65.5%	12973	92	33	103.8	88	8.62	545	8.86	8.02	270.3
2	Tom Brady	NWE	33	702	1068	65.7%	8374	64	17	102.9	41	7.84	261	8.32	7.78	253.8
3	Drew Brees	NOR	47	1224	1807	67.7%	14077	101	50	98.1	58	7.79	412	7.66	7.20	299.5
4	Aaron Rodgers	GNB	47	1003	1552	64.6%	12394	86	31	99.4	115	7.99	730	8.20	7.19	263.7
5	Tony Romo	DAL	35	771	1213	63.6%	9536	63	30	94.8	61	7.86	360	7.79	7.13	272.5
6	Matt Schaub	HTX	43	1012	1537	65.8%	12183	68	37	94.7	80	7.93	524	7.73	7.02	283.3
7	Peyton Manning	CLT	48	1214	1805	67.3%	13202	93	45	95.4	40	7.31	251	7.22	6.93	275.0
8	Kurt Warner	CRD	31	740	1111	66.6%	8336	56	28	95.2	50	7.50	354	7.38	6.75	268.9
9	Ben Roethlisberger	PIT	43	858	1364	62.9%	10829	60	32	92.5	128	7.94	852	7.76	6.53	251.8
10	Eli Manning	NYG	48	945	1527	61.9%	11261	79	49	88.3	73	7.37	507	6.97	6.33	234.6
11	Donovan McNabb	TOT	43	887	1486	59.7%	10846	59	36	85.4	95	7.30	684	7.00	6.15	252.2
12	Matt Ryan	ATL	46	885	1456	60.8%	10061	66	34	86.9	59	6.91	354	6.77	6.27	218.7
13	Kyle Orton	TOT	43	901	1504	59.9%	10427	59	33	84.8	90	6.93	562	6.73	6.00	237.0
14	Joe Flacco	RAV	48	878	1416	62.0%	10206	60	34	87.9	108	7.21	788	6.97	5.96	212.6
15	Brett Favre	TOT	45	923	1411	65.4%	10183	66	48	88.1	86	7.22	599	6.62	5.84	226.3
16	Jay Cutler	TOT	47	981	1603	61.2%	11466	75	60	82.9	98	7.15	625	6.40	5.67	244.0
17	Matt Cassel	TOT	45	860	1459	58.9%	9733	64	34	83.9	115	6.67	644	6.50	5.62	211.6
18	David Garrard	JAX	46	885	1417	62.5%	9951	53	38	84.7	117	7.02	777	6.56	5.56	216.3
19	Jason Campbell	TOT	44	836	1342	62.3%	9250	46	29	85.1	114	6.89	759	6.61	5.57	205.6
20	Carson Palmer	CIN	36	719	1181	60.9%	7795	50	37	81.4	63	6.60	481	6.04	5.34	216.5
21	Ryan Fitzpatrick	TOT	33	603	1040	58.0%	6327	40	34	74.9	83	6.08	465	5.38	4.57	175.8
22	Matt Hasselbeck	SEA	35	668	1141	58.5%	7246	34	44	71.2	80	6.35	503	5.21	4.46	207.0

Provided by Pro-Football-Reference.com: View Original Table

[continue reading…]

Tagged as: Chargers, Norv Turner, Offensive Line, Philip Rivers

{ 14 comments }

Wins with quarterbacks drafted by that team

by Chase Stuart on October 27, 2012

in Draft, Passing, Statistics

Good stat today by ESPN’s Adam Schefter, who notes that Kansas City has gone 25 years without winning a game with a quarterback drafted by the Chiefs. This Todd Blackledge-led victory over the Chargers in 1987 was the last time a quarterback drafted by the Chiefs won a game in red and gold.

That’s remarkable, but as always, we need context. The table below looks at all team wins from 1988 to 2012 and shows how many games were won by a quarterback drafted by that team. Note: For purposes of this post, I’m considering John Elway, Jim Everett, Kelly Stouffer, Eli Manning, and Philip Rivers as having been drafted by the Broncos, Rams, Seahawks, Giants, and Chargers, respectively. Additionally, quarterbacks drafted before 1988 count, but only their wins starting in 1988 count for purposes of the table below. The last two columns show, for each, the quarterback with the most wins among those quarterbacks drafted and not drafted by that team.

Tm	Wins	WbDQB	Perc	MWbDQB	MWbnDQB
NWE	225	212	94.2%	Tom Brady (128)	Doug Flutie (7)
IND	213	181	85.0%	Peyton Manning (141)	Jim Harbaugh (20)
PIT	237	198	83.5%	Ben Roethlisberger (83)	Tommy Maddox (15)
NYG	217	177	81.6%	Eli Manning (74)	Kerry Collins (35)
PHI	225	159	70.7%	Donovan McNabb (92)	Michael Vick (18)
DEN	221	155	70.1%	John Elway (102)	Jake Plummer (39)
TAM	173	117	67.6%	Trent Dilfer (38)	Brad Johnson (26)
CIN	156	104	66.7%	Carson Palmer (46)	Jeff Blake (25)
BUF	203	126	62.1%	Jim Kelly (91)	Drew Bledsoe (23)
SDG	191	118	61.8%	Philip Rivers (66)	Stan Humphries (47)
ATL	184	113	61.4%	Matt Ryan (49)	Chris Chandler (34)
MIA	204	118	57.8%	Dan Marino (99)	Jay Fiedler (36)
WAS	180	104	57.8%	Mark Rypien (45)	Brad Johnson (17)
DAL	204	115	56.4%	Troy Aikman (94)	Tony Romo (50)
NYJ	179	99	55.3%	Chad Pennington (32)	Vinny Testaverde (35)
TEN	216	119	55.1%	Steve McNair (76)	Warren Moon (51)
CLE	127	68	53.5%	Bernie Kosar (29)	Derek Anderson (16)
DET	150	80	53.3%	Rodney Peete (21)	Scott Mitchell (27)
MIN	214	108	50.5%	Daunte Culpepper (38)	Warren Moon (21)
JAX	139	70	50.4%	David Garrard (39)	Mark Brunell (63)
BAL	145	73	50.3%	Joe Flacco (49)	Steve McNair (15)
ARI	149	71	47.7%	Jake Plummer (30)	Kurt Warner (27)
CHI	196	88	44.9%	Jim Harbaugh (35)	Jay Cutler (29)
STL	162	65	40.1%	Jim Everett (38)	Marc Bulger (41)
SFO	229	83	36.2%	Alex Smith (37)	Steve Young (89)
HOU	71	24	33.8%	David Carr (22)	Matt Schaub (38)
GNB	231	69	29.9%	Aaron Rodgers (45)	Brett Favre (160)
CAR	126	32	25.4%	Kerry Collins (22)	Jake Delhomme (53)
SEA	186	36	19.4%	Rick Mirer (20)	Matt Hasselbeck (69)
OAK	177	20	11.3%	Steve Beuerlein (8)	Rich Gannon (45)
NOR	199	2	1.00%	Danny Wuerffel (2)	Drew Brees (64)
KAN	202	0	0.00%	--	Trent Green (48)

As bad as the Chiefs record has been, the Saints record isn’t any better. In fact, since Archie Manning’s last game for the Saints, New Orleans has only drafted two quarterbacks – Dave Wilson and Danny Wuerffel – who have started and won a game for the team. JaMarcus Russell couldn’t even break the Raiders list, ending his career with seven wins. Two other interesting notes. Tony Romo is the only undrafted quarterback in the league currently starting. And of the 32 starting quarterbacks, three of them — Michael Vick, Matt Schaub, and Matt Ryan — were drafted by the Falcons.

Tagged as: quarterbacks, wins

{ 7 comments }

Checkdowns: Josh Freeman is three parts Steve Grogan, one part Eli Manning

by Chase Stuart on October 25, 2012

in Passing, Statistics

Have you taken a look at a passing leaderboard lately? Here’s the PFR passing leaderboard sorted by ANY/A; as always, all columns are sortable.

Rk	QB	Tm	G	Cmp	Att	Cmp%	Yds	TD	TD%	Int	Int%	Y/A	AY/A	Y/C	Sk	Yds	NY/A	ANY/A	Sk%
1	Peyton Manning	DEN	6	154	227	67.8	1808	14	6.2	4	1.8	8	8.4	11.7	10	63	7.4	7.8	4.2
2	Josh Freeman	TAM	6	104	187	55.6	1538	11	5.9	5	2.7	8.2	8.2	14.8	9	65	7.5	7.5	4.6
3	Eli Manning	NYG	7	169	265	63.8	2109	12	4.5	7	2.6	8	7.7	12.5	5	40	7.7	7.4	1.9
4	Robert Griffin III	WAS	7	133	189	70.4	1601	7	3.7	3	1.6	8.5	8.5	12	15	106	7.3	7.4	7.4
5	Drew Brees	NOR	6	166	273	60.8	2097	18	6.6	7	2.6	7.7	7.8	12.6	12	86	7.1	7.2	4.2
6	Ben Roethlisberger	PIT	6	155	235	66	1765	11	4.7	3	1.3	7.5	7.9	11.4	13	72	6.8	7.2	5.2
7	Tom Brady	NWE	7	186	285	65.3	2104	12	4.2	3	1.1	7.4	7.8	11.3	14	96	6.7	7.1	4.7
8	Aaron Rodgers	GNB	7	183	262	69.8	1979	19	7.3	4	1.5	7.6	8.3	10.8	26	142	6.4	7.1	9
9	Matt Schaub	HOU	7	140	222	63.1	1650	10	4.5	4	1.8	7.4	7.5	11.8	8	59	6.9	7	3.5
10	Jake Locker	TEN	4	67	106	63.2	781	4	3.8	2	1.9	7.4	7.3	11.7	3	16	7	6.9	2.8
11	Matt Ryan	ATL	6	160	236	67.8	1756	14	5.9	6	2.5	7.4	7.5	11	13	107	6.6	6.7	5.2
12	Carson Palmer	OAK	6	148	241	61.4	1732	7	2.9	4	1.7	7.2	7	11.7	12	93	6.5	6.3	4.7
13	Alex Smith	SFO	7	127	190	66.8	1427	9	4.7	5	2.6	7.5	7.3	11.2	18	100	6.4	6.2	8.7
14	Joe Flacco	BAL	7	150	252	59.5	1837	9	3.6	6	2.4	7.3	6.9	12.2	18	110	6.4	6.1	6.7
15	Andy Dalton	CIN	7	156	243	64.2	1831	13	5.3	10	4.1	7.5	6.8	11.7	17	102	6.7	5.9	6.5
16	Cam Newton	CAR	6	101	173	58.4	1387	5	2.9	6	3.5	8	7	13.7	15	102	6.8	5.9	8
17	Tony Romo	DAL	6	150	221	67.9	1636	8	3.6	9	4.1	7.4	6.3	10.9	9	59	6.9	5.8	3.9
18	Ryan Fitzpatrick	BUF	7	133	218	61	1435	15	6.9	9	4.1	6.6	6.1	10.8	8	44	6.2	5.7	3.5
19	Christian Ponder	MIN	7	152	227	67	1492	9	4	6	2.6	6.6	6.2	9.8	16	68	5.9	5.5	6.6
20	Sam Bradford	STL	7	131	219	59.8	1592	7	3.2	6	2.7	7.3	6.7	12.2	21	131	6.1	5.5	8.8
21	Ryan Tannehill	MIA	6	118	198	59.6	1454	4	2	6	3	7.3	6.4	12.3	12	109	6.4	5.5	5.7
22	Matthew Stafford	DET	6	164	264	62.1	1754	5	1.9	6	2.3	6.6	6	10.7	12	86	6	5.4	4.3
23	Michael Vick	PHI	6	136	231	58.9	1632	8	3.5	8	3.5	7.1	6.2	12	17	90	6.2	5.4	6.9
24	Andrew Luck	IND	6	134	250	53.6	1674	7	2.8	7	2.8	6.7	6	12.5	16	99	5.9	5.3	6
25	Mark Sanchez	NYJ	7	116	218	53.2	1453	9	4.1	7	3.2	6.7	6	12.5	14	77	5.9	5.3	6
26	Jay Cutler	CHI	6	106	187	56.7	1359	8	4.3	7	3.7	7.3	6.4	12.8	19	121	6	5.3	9.2
27	Russell Wilson	SEA	7	104	175	59.4	1230	8	4.6	7	4	7	6.1	11.8	14	97	6	5.2	7.4
28	Brandon Weeden	CLE	7	154	272	56.6	1783	9	3.3	10	3.7	6.6	5.6	11.6	11	69	6.1	5.1	3.9
29	Philip Rivers	SDG	6	139	209	66.5	1492	10	4.8	9	4.3	7.1	6.2	10.7	18	118	6.1	5.1	7.9
30	Kevin Kolb	ARI	6	109	183	59.6	1169	8	4.4	3	1.6	6.4	6.5	10.7	27	159	4.8	4.9	12.9
31	Matt Hasselbeck	TEN	5	96	156	61.5	931	5	3.2	4	2.6	6	5.5	9.7	10	74	5.2	4.7	6
32	Blaine Gabbert	JAX	6	88	158	55.7	906	6	3.8	3	1.9	5.7	5.6	10.3	15	105	4.6	4.5	8.7
33	Matt Cassel	KAN	5	103	176	58.5	1150	5	2.8	9	5.1	6.5	4.8	11.2	13	74	5.7	4.1	6.9

[continue reading…]

Tagged as: Air Yards, Eli Manning, Josh Freeman, Steve Grogan

{ 1 comment }

More work on POPIP and predicting INT rates

by Chase Stuart on October 23, 2012

in Passing, Statistics

A couple of weeks ago, I wrote about interceptions per incompletion, or POPIP. In that article I showed how a player’s completion percentage is a better predictor of his future interception rate than his actual interception rate. And in this article by Brian Burke, one comment stuck with me:

Griffin has thrown deep, defined as attempts of greater than 15 yards through the air, on only 13% of his attempts, 30th among league quarterbacks. This is also likely the largest factor in his very low interception rate.

That makes sense — quarterbacks throwing short, safe passes should throw fewer interceptions. But this statement is a more important one than you might originally think, thanks to some great research by Mike Clay.

Clay came up with a metric he calls ‘aDOT’ — average depth of target — which measures exactly what you think it does. For each targeted or aimed pass, Pro Football Focus tracks how far from the line of scrimmage the intended target is. What’s makes this stat particularly appealing to me is that it’s very predictable as far as football statistics go. That’s not all that surprising because aDOT is based on a large sample of plays and basically frames how an offense operates.

Clay posted the 10 passers with the largest and smallest aDOT in 2011, which I’ve reproduced below. Note that there are some passes — spikes, throwaways, passes tipped at the line (these are grouped together as ‘other’) — with no target, and therefore are excluded when calculating aDOT. In the far right column, I’ve shown how the player’s aDOT compares to the league average rate of 8.8.

Passer	Yr	Att	Aim	Other	aDOT	lgAVG
Tim Tebow	2011	318	286	32	13.3	151%
Vince Young	2011	114	111	3	11.6	131%
Jason Campbell	2011	165	151	14	10.5	119%
Matt Moore	2011	347	328	19	10.4	118%
Carson Palmer	2011	328	312	16	10.3	117%
Eli Manning	2011	752	698	54	10.1	114%
Cam Newton	2011	517	494	23	10	113%
Joe Flacco	2011	605	568	37	9.8	111%
Ben Roethlisberger	2011	553	529	24	9.8	110%
Chad Henne	2011	112	102	10	9.7	110%
T.J. Yates	2011	189	171	18	9.6	109%
Matt Hasselbeck	2011	518	490	28	8.3	94%
Drew Brees	2011	763	730	33	8.2	93%
Blaine Gabbert	2011	413	381	32	8.1	92%
Alex Smith	2011	513	463	50	8.1	91%
Tony Romo	2011	522	497	25	8.1	91%
Ryan Fitzpatrick	2011	569	544	25	8	90%
Donovan McNabb	2011	156	145	11	7.9	89%
Colt McCoy	2011	463	434	29	7.8	88%
Tyler Palko	2011	135	127	8	7.4	84%
Josh Freeman	2011	551	519	32	7.4	83%

[continue reading…]

Tagged as: aDOT, Interceptions, POPIP, Pro Football Focus

{ 2 comments }

When should the Jaguars give up on Blaine Gabbert?

by Chase Stuart on October 18, 2012

in History, Passing, Statistics

One of the most difficult decisions an organization has to make is when to admit its mistakes. The Jaguars drafted Blaine Gabbert with the 10th overall pick in 2011, and his lack of success is even more striking when compared to the rest of the top dozen selections:

Rd	Pk	Tm	Player	Pos	College/Univ
1	1	CAR	Cam Newton	QB	Auburn
1	2	DEN	Von Miller	LB	Texas A&M
1	3	BUF	Marcell Dareus	DT	Alabama
1	4	CIN	A.J. Green	WR	Georgia
1	5	ARI	Patrick Peterson	CB	LSU
1	6	ATL	Julio Jones	WR	Alabama
1	7	SFO	Aldon Smith	DE	Missouri
1	8	TEN	Jake Locker	QB	Washington
1	9	DAL	Tyron Smith	OT	Tusculum
1	10	JAX	Blaine Gabbert	QB	Missouri
1	11	HOU	J.J. Watt	DE	Wisconsin
1	12	MIN	Christian Ponder	QB	Florida St.

Provided by Pro-Football-Reference.com: View Original Table

Last year, there were three legitimate excuses the Jaguars could proffer to defend Gabbert’s play: he was a rookie, the lockout prevented him from getting proper training, and Jacksonville had the worst set of receivers in the league. Giving up on a first round quarterback after just one season would be silly, especially one where the expectations were that the rookies would struggle. And the cupboard was bare: Jacksonville became the first team since the 2004 Ravens and only the 5th team in the previous 20 seasons to not have a 500-yard wide receiver, so it’s not like Gabbert had a lot to work with. ^[1]Of course, there is the obvious “chicken or the egg” question involved there. The other four teams on that list? The 2004 Ravens (Kyle Boller), 2003 Lions (Joey Harrington), 1997 … Continue reading

But through five games, little has changed in Jacksonville. The Jaguars should wait to evaluate Gabbert’s career — five games into his second season isn’t a fair sample size — but his production so far have been extremely disappointing:

Gabbert is currently 28th in ESPN’s Total QBR, a disappointing start after he ranked last (34th) in that metric in 2011.
Gabbert ranks last in Net Passing Yards per Attempt with an anemic 4.3 average; last season, he also ranked last with a 4.2 NY/A average.

A few years ago, Jason Lisk wrote this post on when the Lions should have given upon Joey Harrington. One of the most relevant points of that article was Lisk’s supposition

that teams are far more likely to commit errors of holding on to a quarterback for too long, while rarely giving up on a quarterback too early — once they have seen him play any amount of time in a real NFL game. I can think of examples of quarterbacks who were drafted, never started for their original team, and found success elsewhere, but its relatively rare to find a quarterback who started but never had success with his original team, and moved elsewhere to have his first breakout.

There were 70 quarterbacks selected in the first round of NFL drafts between 1978 and 2010. How often did a team give up too early on a good quarterback? ^[2]Note that for purposes of this post, I am considering Eli Manning, Philip Rivers, Jim Everett, and John Elway as being drafted by the Giants, Chargers, Rams and Broncos. Vinny Testaverde had success outside of Tampa Bay, but the Bucs didn’t give up “early” on him by any means; he played for six years in Tampa with with varying levels of success. The team did give up too early on Steve Young, although he wasn’t included in this study because he was selected in the supplemental draft. Jim Harbaugh had success in Indianapolis, but it’s not like the Bears didn’t know what they had: Harbaugh was in Chicago for the first seven years of his career.

Jeff George had good years outside of Indianapolis, but I wouldn’t say the Colts gave up early on him. He was inconsistent for four years and caused problems off the field; he was finally traded in connection with a holdout. Mike Vick has had success in Philadelphia, but the Falcons obviously had their hands forced when they gave up on him. Ditto Kerry Collins, whose off the field issues left the Panthers with little choice.

With the exception of Steve Young, who Tampa traded after two years — and who may not have ever turned into a star quarterback in Tampa Bay — you’d be hard pressed to find any examples of teams giving up on first round picks too early (with the exception of those released/traded for nonfootball reasons). Chad Pennington had one great year in Miami, but that was after a long career in New York. Doug Williams and Trent Dilfer won Super Bowls with other teams, but Tampa Bay didn’t give up on either quarterback too early by any reasonable definition of the phrase. The reality is, teams will do just about everything before giving up on a first round quarterback too early and as a result, take way too long to move on from a bad investment. And while teams are (understandably) deathly afraid of giving up on a highly drafted quarterback too early, they’re more likely to harm themselves by waiting to move on for too long on a bad investment.

Through six weeks, NFL teams are averaging 6.44 NY/A, meaning Gabbert is averaging only 67% as many net yards per attempt as the average passer. How does that compare historically? The table below shows all drafted quarterbacks who threw at least 250 passes in their second season, and lists their NY/A and NY/A relative to league average during their sophomore years:

QB	Year	Tm	Att	NY/A	NY/A LgAv	Rd.Ovrl
Dan Marino	1984	MIA	564	8.6	146%	1.27
Ben Roethlisberger	2005	PIT	268	7.8	131%	1.11
Daunte Culpepper	2000	MIN	474	7.4	127%	1.11
Peyton Manning	1999	IND	533	7.3	126%	1.1
Eric Hipple	1981	DET	279	7	117%	4.85
Boomer Esiason	1985	CIN	431	6.8	117%	2.38
Jay Cutler	2007	DEN	467	6.8	112%	1.11
Matt Robinson	1978	NYJ	266	6	109%	9.227
Bernie Kosar	1986	CLE	531	6.3	107%	1.1
David Carr	2003	HOU	295	6.2	106%	1.1
Josh Freeman	2010	TAM	474	6.5	105%	1.17
Kerry Collins	1996	CAR	364	6.1	105%	1.5
Trent Edwards	2008	BUF	374	6.4	105%	3.92
Brett Favre	1992	GNB	471	6	104%	2.33
Eli Manning	2005	NYG	557	6.1	104%	1.1
Drew Bledsoe	1994	NWE	691	6.2	104%	1.1
Doug Williams	1979	TAM	397	5.9	103%	1.17
Joe Flacco	2009	BAL	499	6.3	103%	1.18
Jim Everett	1987	RAM	302	6	103%	1.3
John Elway	1984	DEN	380	6	103%	1.1
Gus Frerotte	1995	WAS	396	6.1	103%	7.197
Michael Vick	2002	ATL	421	6	102%	1.1
Brian Griese	1999	DEN	452	6	102%	3.91
Rodney Peete	1990	DET	271	6	101%	6.141
Vinny Testaverde	1988	TAM	466	5.9	100%	1.1
Charlie Batch	1999	DET	270	5.8	99%	2.60
Joe Montana	1980	SFO	273	5.9	99%	3.82
Byron Leftwich	2004	JAX	441	6.1	99%	1.7
Tom Brady	2001	NWE	413	5.8	99%	6.199
Craig Erickson	1993	TAM	457	5.7	99%	4.86
Jake Plummer	1998	ARI	547	5.8	98%	2.42
Timm Rosenbach	1990	PHO	437	5.9	98%	1.2
Tony Eason	1984	NWE	431	5.8	98%	1.15
Matt Ryan	2009	ATL	451	6	97%	1.3
Tarvaris Jackson	2007	MIN	294	5.9	97%	2.64
Tony Banks	1997	STL	487	5.5	97%	2.42
Chuck Long	1987	DET	416	5.7	97%	1.12
David Woodley	1981	MIA	366	5.8	97%	8.214
Vince Young	2007	TEN	382	5.9	97%	1.3
Carson Palmer	2004	CIN	432	5.9	97%	1.1
Drew Brees	2002	SDG	526	5.6	96%	2.32
Jim McMahon	1983	CHI	295	5.7	95%	1.5
Mark Sanchez	2010	NYJ	507	5.8	95%	1.5
Billy Joe Tolliver	1990	SDG	410	5.7	95%	2.51
Alex Smith	2006	SFO	442	5.6	94%	1.1
Mike Pagel	1983	BAL	328	5.6	94%	4.84
Steve Walsh	1990	NOR	336	5.6	94%	1.1
Shaun King	2000	TAM	428	5.4	93%	2.50
Neil O'Donnell	1991	PIT	286	5.5	93%	3.70
Chad Henne	2009	MIA	451	5.7	92%	2.57
Patrick Ramsey	2003	WAS	337	5.3	92%	1.32
David Whitehurst	1978	GNB	328	5.1	92%	8.206
JaMarcus Russell	2008	OAK	368	5.5	90%	1.1
Don Majkowski	1988	GNB	336	5.3	89%	10.255
Tyler Thigpen	2008	KAN	420	5.5	89%	7.217
Trent Dilfer	1995	TAM	415	5.3	89%	1.6
Danny Kanell	1997	NYG	294	5	88%	4.130
Troy Aikman	1990	DAL	399	5.2	88%	1.1
Marc Wilson	1981	OAK	366	5.2	87%	1.15
Todd Blackledge	1984	KAN	294	5.1	87%	1.7
John Friesz	1991	SDG	487	5.2	87%	6.138
Chris Miller	1988	ATL	351	5.1	87%	1.13
Donovan McNabb	2000	PHI	569	5.1	87%	1.2
Steve Fuller	1980	KAN	320	5.2	86%	1.23
Browning Nagle	1992	NYJ	387	5	86%	2.34
Joey Harrington	2003	DET	554	5	86%	1.3
Charlie Frye	2006	CLE	392	5	84%	3.67
Kellen Clemens	2007	NYJ	250	5	83%	2.49
Cade McNown	2000	CHI	280	4.8	82%	1.12
Rick Mirer	1994	SEA	381	4.9	82%	1.2
Colt McCoy	2011	CLE	463	5.2	82%	3.85
Steve DeBerg	1978	SFO	302	4.4	80%	10.275
Phil Simms	1980	NYG	402	4.8	80%	1.7
Tim Tebow	2011	DEN	271	4.9	78%	1.25
David Klingler	1993	CIN	343	4.5	78%	1.6
Sam Bradford	2011	STL	357	4.9	77%	1.1
Kyle Boller	2004	BAL	464	4.6	75%	1.19
Jeff George	1991	IND	485	4.5	75%	1.1
Andrew Walter	2006	OAK	276	4.4	74%	3.69
Akili Smith	2000	CIN	267	3.5	60%	1.3

If your quarterback plays poorly in his second year, you’re basically hoping he’s Phil Simms (who had his first strong season at age 30) or the good version of Jeff George. Maybe Sam Bradford or [gasp] Tim Tebow, will also become solid starters in the NFL one day. But that’s only one part of the equation, and it’s the minor half. You could have the next Akili Smith or Kyle Boller or David Klingler or Colt McCoy or Rick Mirer or Cade McNown or Joey Harrington, too.

You might think it’s far better to wait a year too long with a first round investment than to cut bait a year too early. Tell that to the Ravens, who after two years of Kyle Boller, chose to wait it out in the 2005 draft and selected Mark Clayton over Aaron Rodgers (why take Rodgers, Cal quarterbacks are terrible!). Detroit selected Joey Harrington with the third pick in the 2002 draft, but as Lisk noted, Detroit could have reasonably “given up” (more on this in a second) on Harrington by the end of the 2003 season. The Lions did not, and selected Roy Williams in the 2004 draft instead of say, Ben Roethlisberger.

And “give up” doesn’t necessarily mean cut or spend a first round pick on another quarterback. Assuming Joe Flacco re-signs with Baltimore, there won’t be any real options in free agency for the Jaguars to address the quarterback position (Jason Campbell is probably the best of the bunch). But they can certainly address the issue in the draft. If a quarterback the Jaguars’ scouts view as elite is available with their (potentially very high) first round pick, then I don’t think you can simply say “let’s give Blaine one more year.” But at a minimum, the Jaguars must spend a pick on a quarterback in the 2013 draft if Gabbert doesn’t improve over the rest of 2012.

References[+]

References
↑1	Of course, there is the obvious “chicken or the egg” question involved there. The other four teams on that list? The 2004 Ravens (Kyle Boller), 2003 Lions (Joey Harrington), 1997 Buccaneers (Trent Dilfer) and 1992 Bengals (Boomer Esiason/David Klingler) featured four first round quarterbacks who ended up being busts.
↑2	Note that for purposes of this post, I am considering Eli Manning, Philip Rivers, Jim Everett, and John Elway as being drafted by the Giants, Chargers, Rams and Broncos.

Tagged as: AFC South, Blaine Gabbert, Jaguars

{ 17 comments }

Checkdowns: Patriots Passing Game Struggles

by Chase Stuart on October 17, 2012

in Passing, Uncategorized

If there was one thing you can count on in New England, it’s that the Patriots passing attack would be more efficient than their opponent’s nearly every week. From 2003 to 2011, New England averaged 6.9 net yards per pass attempt while their defense allowed 6.0 NY/A. But this season, the Patriots passing offense is struggling by New England standards while the pass defense is worse than ever. Take a look: ^[1]Note that the table below lists team passing yards, which already deducts sack yardage lost

Year	Att	Yds	Sk	Opp_Att	Opp_Yds	Opp_Sk	NY/A	NY/A A	Diff
2012	243	1758	13	219	1733	11	6.9	7.5	-0.7
2011	612	5084	32	619	4703	40	7.9	7.1	0.8
2010	507	3847	25	611	4136	36	7.2	6.4	0.8
2009	592	4436	18	512	3355	31	7.3	6.2	1.1
2008	536	3569	46	474	3219	31	6.1	6.4	-0.2
2007	586	4731	21	526	3041	47	7.8	5.3	2.5
2006	527	3400	29	518	3203	44	6.1	5.7	0.4
2005	564	4120	28	527	3703	33	7	6.6	0.3
2004	485	3588	26	538	3400	45	7	5.8	1.2
2003	537	3432	32	618	3232	41	6	4.9	1.1
2002	605	3577	31	531	3179	34	5.6	5.6	0
2001	482	3089	46	546	3497	41	5.9	6	-0.1
2000	565	3181	48	544	3522	29	5.2	6.1	-1

Playing the Jets on Sunday is the perfect medicine for a NY/A-imbalance, but what do you make of New England’s struggles this year?

References[+]

References
↑1	Note that the table below lists team passing yards, which already deducts sack yardage lost

Tagged as: AFC East, Patriots, Tom Brady

{ 3 comments }

Extreme Outliers: Rookie Edition

by Chase Stuart on October 12, 2012

in Passing, Statistics

Griffining: Playing for a coach that tries to help you.

Both Andrew Luck and Robert Griffin III have been very successful this year. Griffin ranks 2nd in Y/A, 2nd in AY/A, 4th in NY/A, and 4th in ANY/A, an incredible performance nearly across the board (he’s 23rd in sack rate) by the Redskins rookie. He also is leading the league with a 69.1% completion rate and ranks 5th in passer rating. Luck ranks only 23rd in Y/A, 22nd in AY/A, 21st in NY/A, and 18th in ANY/A, respectable numbers for a rookie but on the surface, little more than that. He does rank 7th in sack rate, which is an excellent sign, but he ranks last in the NFL in completion percentage (in the non-Mark Sanchez division) and only 25th in passer rating.

But there are some other stats out there that paint a different picture. ESPN’s Total QBR ranks Griffin 11th overall — slightly below most of his other metrics — but ranks Luck as the fourth most effective quarterback so far this season. Also, despite Griffin’s edge in most metrics, the Colts and Redskins are essentially tied in three key drive metrics — points per drive, yards per drive and drive success rate — and I don’t think that’s because Donald Brown is so awesome. As Nate Dunlevy pointed out to me, one reason for this is that Luck has accumulated a large number of rushing first downs: Luck is tied for the league lead with Arian Foster on third down rushes that resulted in a first down. And once you account for strength of schedule, Luck vaults to #1 on the QBR list.

But let’s put aside effectiveness for right now. Some advanced metrics show you that they’ve been skinning cats in very different ways:

According to Advanced NFL Stats, Luck has thrown a pass 15 yards past the line of scrimmage on 24.3% of his throws, the 5th highest rate in the league. Griffin ranks 32nd with a deep rate of just 12.2%, ahead of only Matt Hasselbeck.
If you completely removed Yards After the Catch from the equation, Luck would rank in the top 10 at 4.5 yards per attempt while Griffin would rank 25th with just 3.5 yards per attempt.
Griffin ranks third behind just Christian Ponder and Philip Rivers when it comes to percentage of passing yards that are due to YAC, at 58.7%; Luck ranks 32nd, ahead of only John Skelton and Mark Sanchez, with only 33.4% of his yards coming on yards after the catch by his receivers.
According to Footballguys.com’s subscriber content, the Colts have targeted their wide receivers on 72.1% of their passes, the second highest rate in the league behind the Rams. The Colts are also last in the league with only 6.4% of their passes aimed at running backs (this also jives with the numbers from Mike Clay of Pro Football Focus.). The Redskins are more middle of the road in these metrics, but Andrew Luck is being forced to rely on his wide receivers with no real receiving threat in the backfield to help him out. As a result, it’s probably not too surprising that his completion percentage is so low.

Luck has also excelled in the two-minute drill and no-huddle situations early this year, although Griffin has been no slouch in those departments, either. But it’s clear that the Colts — rightly or wrongly — aren’t treating Luck with kid gloves. In fact, one could argue that they’re treating him no differently than they did Peyton Manning. Luck is averaging 44.3 pass attempts per game so far this season, second behind only Drew Brees. With a mediocre defense and a bad running game, the Colts are basically putting each game in the hands of Luck to win. Griffin is averaging only 27.8 pass attempts per game right now, and the Redskins have done a fantastic job molding the offense to to suit Griffin’s strengths.

Griffin’s numbers are better right now — ESPN excluded, of course — but that may be a reflection that the Shanaclan is more nurturing than Bruce Arians. Griffin’s success is outstanding, but Luck has been doing just as well under much more challenging conditions.

Update: Jeff Bennett, one of the creators behind ESPN’s Total QB, e-mailed me some notes this morning:

We break rushing out into two categories, scrambles and designed rushes. The quarterback receives more credit for scrambles then designed rushes – the reason being designed rushes are, well, designed to help the quarterback get more yards on the rush. Scrambles are not. Whatever positive or negative that comes from those is mostly on the quarterback.

So back to Luck. He has nine first down rushes this season on scrambles, most in the NFL. Seven of the nine have come on 3rd down, which generally is more important since the alternative to not picking up a 1st down is likely a punt instead of 2nd or 3rd down. No one else in the league has more than three 1st down rushes on scrambles.

Luck’s average pass is traveling 9.8 yards downfield this season. That is the third longest average pass distance in the league (behind Joe Flacco and Jay Cutler). Griffin averages 7.2 yards, a full yard below league average.

The average quarterback this season is getting 56% of their passing yards via “air yards” (meaning 44% of yards are coming after the catch). Griffin has 43% of his yards through the air. Luck has 68%.

Tagged as: Andrew Luck, Colts, Redskins, RG3

{ 3 comments }

Re-post: Analyzing Drew Brees’ pursuit of Johnny Unitas’ legendary streak

by Chase Stuart on October 5, 2012

in Passing

In August, I wrote this article examining Drew Brees’ pursuit of Johnny Unitas’ streak of 47 consecutive games with a touchdown pass. Brees tied the record last weekend and is set to break the tie Sunday night. If you missed this article the first time, or just wanted to re-read as we approach the record-setting day, here’s the link.

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Quarter-by-Quarter Team Win Probability Added

by Neil Paine on October 4, 2012

in History, Passing, Statistics

A couple of weeks ago, I wrote about a method of calculating a team’s win probability at the end of any given quarter, given the pregame Vegas line and the score margin of the game after the quarter in question. Today, I want to break down those numbers in more detail by looking at which teams (and quarterbacks) added the most Win Probability in each stage of the game.

To compute Win Probability Added (WPA) for the purposes of this post, you look at how much the team’s chances of winning changed from one quarter to the next. For instance, here’s how I’d deconstruct Monday night’s game for the winning Bears:

Date	Tm		Opp	QB	WPA_loc	WPA_vegas	WPA_1st	WPA_2nd	WPA_3rd	WPA_4th	WPA_ot	WPA_tot
10/1/2012	Chi	@	Dal	Jay Cutler	-0.079	-0.021	+0.013	+0.137	+0.420	+0.029	+0.000	+0.500

WPA_loc and WPA_vegas are the two components that make up the pregame win expectancy. Chicago was on the road here, which typically deducts about 8% from a team’s base 50% WP right from the get-go (or roughly 2.5-3.0 points of spread), and on top of that they were 3.5-point underdogs, which put their pregame WP another 2.1% lower than you’d expect from an evenly-matched road team. All told, before the opening kickoff, they were already down about 10% in terms of WP.

Then both teams had a scoreless first quarter, which added 1.3% to Chicago’s total under the WPA_1st banner. This happened because, even though they were still tied, there was less time remaining in the game during which Dallas could exert their theoretical talent advantage (the variance of the future was likely to be higher, which always favors the underdog).

Chicago took a 10-7 lead in the 2nd quarter, which tacked on 13.7% of WP, as seen under WPA_2nd. By this point, they had erased their early 10% deficit and were actually favored to win with a WP of 55.1%. A 14-3 3rd period was the killer, though, adding 42% of WP in the WPA_3rd column. Going into the final quarter with a 24-10 lead, the Bears had a 97.1% chance of winning; when they didn’t relinquish that lead, the remaining 2.9% of WP were added under WPA_4th, since the game was over.

And as is the case with every winning team ever, their WPA_tot for the game was +0.500.

See how it works? By using WPA in this manner, we can detect when in the course of the game a team adds or subtracts the most from its chances of victory. We can also add these WPA numbers up across games at the season level, or even for entire careers.

[continue reading…]

Tagged as: WPA

{ 13 comments }

Interceptions per Incompletion (or POPIP)

by Chase Stuart on September 24, 2012

in Passing, Statistics, Theory

The closest I'm willing to get with a baseball photo.

I leave the baseball analysis to my brothers at baseball-reference.com, but I know enough to be dangerous. There’s a stat called BABIP, which stands for Batting Average on Balls In Play. A “ball in play” is simply any at bat that doesn’t end in a home run or a strikeout. The thinking goes that luck and randomness is mostly responsible for the variance in BABIP allowed by pitchers to opposing batters. Pitchers can control the number of strikeouts they throw and control whether they allow home runs or not, but they can’t really control their BABIP.

Therefore, if a pitcher has a high BABIP, sort of like an NFL team with a lot of turnovers, he’s probably been unlucky. And good things may be coming around the corner. A high BABIP means a pitcher probably has an ERA higher than he “should” and that his ERA will go down in the future. In fact, you can easily recalculate a pitcher’s ERA by replacing the actual BABIP he has allowed with the league average BABIP. And that ERA will be a better predictor of future ERA than the actual ERA. At least, I think. Forgive me if my baseball analysis is not perfect.

Are you still awake? It’s Monday, and I’ve brought not only baseball into the equation, but obscure baseball statistics. Let’s get to the point of the post by starting with a hypothesis:

Assume that it is within a quarterback’s control as to whether he throws a completed pass on any given pass attempt. However, if he throws an incomplete pass, then he has no control over whether or not that pass is intercepted.
[continue reading…]

Tagged as: Brett Favre, Donovan McNabb, Interceptions, Kurt Warner

{ 14 comments }

Jim Harbaugh has turned Alex Smith into Jim Harbaugh 2.0

by Chase Stuart on September 21, 2012

in Coaches, Passing

The teacher and the pupil.

Alex Smith has had an incredible career revival since Jim Harbaugh came to San Francisco. The first six seasons of his career, Alex Smith won just 38% of his 50 starts, but he has an incredible 15-3 regular season record since 2011 (83%). From 2005 to 2012, Smith had an ugly 72.1 passer rating, the worst of any quarterback with 1500 attempts over that span. Since Harbaugh came to town, Smith has a 93.6 passer rating, the 7th best mark of any quarterback over that time frame.

But there are two other, related, metrics, that indicate a fundamental shift in Smith’s style of play. In 2011, Alex Smith led the NFL in interception rate, but he also led the league in sacks. Smith threw an interception on just 1.1% of his passes in 2011 but took a sack on 9.0% of his dropbacks; this year, his sack rate has jumped to 10.9% while he has yet to thrown an interception.

Last year, the average quarterback threw an interception on 2.9% of his passes and was sacked on 6.4% of his dropbacks, meaning Smith’s interception rate was just 39% of the league average while his sack rate was 41% higher than league average. Smith also averaged just 197 passing yards per start, 80% of the league average metric.

It’s extremely early, of course, but Smith looks to be on a similar path this year. Which made me wonder: how often does a quarterback ^[1]For purposes of this study, I also limited the group to quarterbacks since 1978 who played for the same team for both years and who threw at least 200 passes in both years. have a two-year stretch with (1) an excellent interception rate, (2) a bad sack rate, and (3) a below-average amount of passing yards per game? The answer is very rarely.

There’s a lot of information to present, so I’ve overloaded the table below. This lists all quarterbacks since 1978 who over a two-year period had a sack rate at least 30% higher than average, an interception rate of 70% of league average or lower, and were below league average in passing yards per game. After the traditional categories, I’ve listed each quarterback’s sack rate, interception rate and yards per game, and then how their sack rates, interception rates and yards per game compared to league average. The last two columns show the quarterback’s record over those two years.

QB	Tm	Years	Att	Yd	TD	INT	Sk	SkYd	SkRt	INTRt	YPG	Sk%	INT%	YPG%	Rec	Win%
Charlie Batch	DET	1998--1999	573	4135	24	13	73	408	11.3%	2.3%	180	159.9%	68.3%	80.1%	11-11-0	0.500
Steve Young	SFO	1996--1997	672	5439	33	12	69	380	9.3%	1.8%	201	134.6%	55.6%	91.5%	21-6-0	0.778
Jim Harbaugh	IND	1996--1997	714	4690	23	15	77	446	9.7%	2.1%	180	140.7%	65.4%	81.9%	9-16-0	0.360
Jim Harbaugh	IND	1995--1996	719	5205	30	16	72	409	9.1%	2.2%	179	145.3%	69.2%	78.6%	14-12-0	0.538
Jim Harbaugh	IND	1994--1995	516	4015	26	11	53	291	9.3%	2.1%	149	156.2%	69%	64.3%	11-10-0	0.524
Ken O'Brien	NYJ	1987--1988	817	5263	28	15	87	631	9.6%	1.8%	202	134%	46.6%	91.9%	11-12-1	0.479
Neil Lomax	STL	1985--1986	892	5797	31	24	113	823	11.2%	2.7%	193	141.2%	65.9%	85.8%	9-20-1	0.317
Ken O'Brien	NYJ	1984--1985	691	5290	31	15	84	567	10.8%	2.2%	203	130.1%	52.8%	89.9%	12-9-0	0.571
Steve Bartkowski	ATL	1983--1984	701	5325	33	15	91	648	11.5%	2.1%	213	140.5%	50.8%	94.6%	9-16-0	0.360
Neil Lomax	STL	1982--1983	559	4003	29	17	74	549	11.7%	3%	182	147.7%	69.6%	82%	12-9-1	0.568

During Jim Harbaugh’s 4 years in Indianapolis, he was essentially Alex Smith. He had a 9.6% sack rate and a 2.1% interception rate, while averaging under 180 passing yards per game. When discussing Joe Namath, I noted that he almost never took sacks, which by some measures penalized him because it drove down his completion percentage and increased his interception rate. You can put Alex Smith and the Indianapolis version of Jim Harbaugh on one end of a spectrum and Joe Namath on the other. Both interceptions and sacks are bad, but to some extent, quarterbacks can decide whether they want to throw interceptions or take sacks. Smith, under Harbaugh’s tutelage, has clearly chosen the latter.

On a team with a great defense, that can work. Namath’s defenses weren’t always good, but when they were, the Jets were Super Bowl contenders. When the defenses struggled, Namath pressed even more, and ended up throwing even more interceptions. Smith is never asked to do too much, and Harbaugh has surrounded him with enough talent on the other side of the ball to make that a winning formula.

From 1994 to 1996, Jim Harbaugh went just 20-26 with the Colts. In 1997, Harbaugh had the lowest interception rate in the NFL and the second highest sack rate in the league. But the 1997 Colts ranked in the bottom 5 of the NFL in points allowed, passing touchdowns allowed, interceptions forced, rushing yards allowed, rushing touchdowns allowed and yards per carry allowed. The team went 3-13 overall, and 2-9 with Harbaugh, indicating that this conservative philosophy has its limitations.

Often times we use stats as a way to rank players, where more of one stat or less of another means a player is good, and less of one stat and more of another means a player is bad. But stats can also be used descriptively without overarching themes of good or bad. Just like some running backs are big and slow and others are small and fast, some quarterbacks are risky and some are risk-averse.

Harbaugh clearly was a risk-averse player in Indianapolis under Lindy Infante. What about the other players on the list? Conservative and risk-averse were good adjectives to describe Charlie Batch’s first two years in the league. In 1998, he had Barry Sanders, but Batch’s numbers were nearly identical both seasons (of course, you would normally expect some improvement by a quarterback betwen year one and two). It looks like he played things very safe as a rookie on a good team in 1998, and let’s not forget how he got the starting job: Scott Mitchell was benched after throwing a pick-six in overtime. We can safely conclude that Batch was told to avoid interceptions at all costs, for many reasons.

Steve Young led the league in passer rating in ’96 and ’97, and for many reasons, doesn’t really feel like a comparable player to Alex Smith. He had already been a two-time MVP by 1996.

Ken O’Brien was a very accurate quarterback who led the league in interception rate in ’85, ’87 and ’88. But he took a ton of sacks, in part because of a below-average offensive line. At his peak he was better than Smith has been so far — in ’85 he was 2nd in yards per attempt and he was 5th in that metric in ’86 — but there are some similarities between the two players.

From 1982 to 1986, Neil Lomax had a 10.5% sack rate but a tiny 2.8% interception rate; despite the conservative nature, his team went just 30-36-2 over that span. Lomax was outstanding in 1984, but otherwise was a solid but unspectacular player during this span (Lomax made the Pro Bowl in ’87 when he led the league in completions, attempts, and passing yards.) Lomax also benefited from consecutive All-Pro seasons from Roy Green in ’83 and ’84, but poor defenses prevented Lomax from compiling a winning record in St. Louis.

In the early ’80s, Steve Bartkowski had some success under Leeman Bennett, and made the Pro Bowl in ’80 and ’81. During those years, he was at or above average in sack rate and also interception rate, but then his interception rate improved dramatically in ’83 while his sack rate fell off for the rest of his career. A likely explanation is the hiring of Dan Henning that season, who may have emphasized a more conservative approach.

The two years before Harbaugh arrived, Smith had a 6.2% sack rate and a 3.1% interception rate, both numbers which were pretty close to league average. But Alex Smith 2.0 is not trying to prove to the world that he’s the #1 pick who can do everything; this version is concerned with minimizing risks at all costs. So far, it’s been a very successful formula.

References[+]

References
↑1	For purposes of this study, I also limited the group to quarterbacks since 1978 who played for the same team for both years and who threw at least 200 passes in both years.

Tagged as: 49ers, Alex Smith, Jim Harbaugh

{ 4 comments }

The Biggest Quarter-by-Quarter Comebacks Since 1978

by Neil Paine on September 20, 2012

in History, Passing, Statistics, Trivia

[Today is a two-post day at Football Perspective. Check here for my week 2 power rankings, while Neil provides an innovative look at the biggest comebacks of the last 35 years in this post. — Chase

In my last post, I introduced a method of estimating the home team’s pre-game win probability in Excel using the Vegas spread:

p(W) = (1-NORMDIST(0.5,-(home_line),13.86,TRUE)) + 0.5*(NORMDIST(0.5,-(home_line),13.86,TRUE)-NORMDIST(-0.5,-(home_line),13.86,TRUE))

The Comeback ranks as the 2nd most impressive comeback after two quarters, but only 20th overall.

Let me explain the rationale behind the scary-looking equation. The first part represents the probability that the home team ends regulation time with a lead of 1 point or more, using Hal Stern’s finding that the home team’s final margin of victory can be approximated by a normal random variable with a mean of the Vegas line and a standard deviation of 13.86. The second part is the probability that regulation ends in a tie, multiplied by 0.5 (this assumes each team has roughly a 50-50 chance of winning in overtime).

With a small twist, we can also apply this formula within games, to the line-score data for every quarter. Within a game, the home team’s probability becomes:

p(W) = (1-NORMDIST(away_margin+0.5,-home_line*(minleft/60),13.86/SQRT(60/minleft),TRUE))+0.5*(NORMDIST(away_margin+0.5,-home_line*(minleft/60),13.86/SQRT(60/minleft),TRUE)-NORMDIST(away_margin-0.5,-home_line*(minleft/60),13.86/SQRT(60/minleft),TRUE))

This is the same equation as before, but we’re adding in Home_Margin (home team pts minus road team pts for the game, through the end of the quarter in question), reducing the effect of the home Vegas line linearly based on how much time remains in the game, and changing the standard deviation of scoring margin to become:

Stdev = 13.86 / sqrt(60 / n)

where n = the number of minutes remaining in the game.

These changes will help us estimate a team’s chances of winning at the end of each quarter. For instance, Monday night’s game — where the Falcons were a 3-point home favorite over the Broncos — goes from:

Team	1st	2nd	3rd	4th	Total
Atlanta	10	10	7	0	27
Denver	0	7	0	14	21

To this:

Team	Pregame	After 1st	At Half	After 3rd	Final
Atlanta	58.6%	84.6%	93.0%	99.9%	100.0%
Denver	41.4%	15.4%	7.0%	0.1%	0.0%

[continue reading…]

{ 7 comments }

Giants-Cowboys is another referendum on Manning and Romo

by Chase Stuart on September 5, 2012

in Passing, Statistics

The third and fourth most popular quarterbacks in New York this week.

There are few nights as precious as tonight, the official start of the 2012 regular season. Even after tonight, 255 regular season games remain for us to enjoy. As usual, the defending Super Bowl champion hosts the opening game, and it didn’t take the NFL schedule makers long to decide on an opponent. This will be the 6th time in 8 meetings that the Giants and Cowboys will meet on primetime television. And as usual, the media will turn this game into another referendum on Tony Romo and Eli Manning.

Public perception says that Manning is the better quarterback, based ~~largely~~ exclusively on his post-season success and reputation as a clutch quarterback. And there’s a good reason he has such a reputation: Manning has won 8 of his last 9 playoff games and tied NFL single-season records with seven 4th-quarter comebacks and eight game-winning drives in 2011. Romo has a reputation as the chokiest of chokers, is 1-3 in playoff games, and has been less stellar than Manning late in games. While Manning has 21 career 4th quarter comebacks and is 21-22 in games where he had an opportunity for a 4th quarter comeback, Romo is just 13-20 in 4th quarter comeback opportunities. But let’s leave that to the side for now.

Because based on their regular season statistics, Romo absolutely crushes Manning, at least statistically. The gap shrunk significantly in 2011, but Romo’s track record of production and efficiently is considerably more impressive. Manning entered the league in 2004 but struggled his first three years; Romo first started in 2006 and was above average immediately. But let’s just focus on the past five seasons. The table below displays the statistics each quarterback produced from 2007 to 2011. Note that since Romo has missed time due to injury, I have added a third row, which pro-rates Romo’s numbers to 80 starts:
[continue reading…]

Tagged as: Cowboys, Eli Manning, Giants, NFC East, Tony Romo

{ 38 comments }

The Greatest QB of All-Time IV, Part III: Playoff Results

by Chase Stuart on August 31, 2012

in G.O.A.T., History, Passing, Statistics

The original standard for postseason success.

On Wednesday, I explained the methodology for grading each quarterback in each season. Yesterday, I came up with an all-time career list of the best quarterbacks based on their regular season play. Today, a look at playoff performances.

Using the same formula, we can grade each quarterback in each game and adjust for era ^[1]Note that I do not have individual playoff sack data prior to 2008, so I am using pro-rated sack numbers based on team sack data.. However, it should be obvious that the sample sizes here are incredibly small, and the stats are even less likely to tell the true story when looking at just one game. Strength of schedule becomes a significant factor here, as well. But, caveats aside, there’s a lot we can do with playoff data. For example, we can rank every quarterback performance in Super Bowl history:

Rk	QB	Tm	Opp	SB	W/L	Att	Pyd	TD	INT	CY	CYP	VAL
1	Joe Montana	SFO	MIA	19	W	35	331	3	0	406	11	272
2	Steve Young	SFO	SDG	29	W	36	325	6	0	431	11.1	264
3	Troy Aikman	DAL	BUF	27	W	30	273	4	0	381	12.3	258
4	Joe Montana	SFO	DEN	24	W	29	297	5	0	397	13.3	256
5	Kurt Warner	STL	TEN	34	W	45	414	2	0	447	9.7	225
6	Jim Plunkett	OAK	PHI	15	W	21	261	3	0	320	14.5	219
7	Phil Simms	NYG	DEN	21	W	25	268	3	0	323	12.4	216
8	Doug Williams	WAS	DEN	22	W	29	340	4	1	358	11.6	211
9	John Elway	DEN	ATL	33	W	29	336	1	1	331	11	181
10	Jim McMahon	CHI	NWE	20	W	20	256	0	0	284	11.6	174
11	Joe Montana	SFO	CIN	23	W	36	357	2	0	351	9	165
12	Jake Delhomme	CAR	NWE	38	L	33	323	3	0	325	8.8	146
13	Tom Brady	NWE	CAR	38	W	48	354	3	1	369	7.7	141
14	Terry Bradshaw	PIT	DAL	13	W	30	318	4	1	266	7.8	140
15	Mark Rypien	WAS	BUF	26	W	33	292	2	1	287	8.7	128
16	Terry Bradshaw	PIT	RAM	14	W	21	309	2	3	214	10.2	123
17	Bart Starr	GNB	KAN	1	W	23	250	2	1	224	8.7	121
18	Terry Bradshaw	PIT	DAL	10	W	19	209	2	0	200	9.5	121
19	Aaron Rodgers	GNB	PIT	45	W	39	304	3	0	348	8.3	118
20	Brett Favre	GNB	NWE	31	W	27	246	2	0	268	8.1	111
21	Drew Brees	NOR	IND	44	W	39	288	2	0	321	8	107
22	Ken Stabler	OAK	MIN	11	W	19	180	1	0	183	8.7	103
23	Troy Aikman	DAL	PIT	30	W	23	209	1	0	218	8.7	91
24	Kurt Warner	ARI	PIT	43	L	43	377	3	1	329	7.3	87
25	John Elway	DEN	NYG	21	L	37	304	1	1	270	6.5	81
26	Bart Starr	GNB	OAK	2	W	24	202	1	0	182	6.5	79
27	Joe Montana	SFO	CIN	16	W	22	157	1	0	188	7.8	76
28	Tom Brady	NWE	PHI	39	W	33	236	2	0	259	7.4	75
29	Joe Namath	NYJ	BAL	3	W	28	206	0	0	195	6.5	68
30	Peyton Manning	IND	NOR	44	L	45	333	1	1	308	6.8	67
31	Ken Anderson	CIN	SFO	16	L	34	300	2	2	254	6.4	67
32	Jeff Hostetler	NYG	BUF	25	W	32	222	1	0	234	6.9	66
33	Bob Lee	MIN	OAK	11	L	9	81	1	0	100	10.9	65
34	Roger Staubach	DAL	MIA	6	W	19	119	2	0	140	6.7	63
35	Steve McNair	TEN	STL	34	L	36	214	0	0	208	5.6	61
36	Eli Manning	NYG	NWE	46	W	40	296	1	0	302	7	61
37	Terry Bradshaw	PIT	MIN	9	W	14	96	1	0	104	6.5	59
38	Kurt Warner	STL	NWE	36	L	44	365	1	2	287	6	55
39	Roger Staubach	DAL	PIT	13	L	30	228	3	1	161	4.6	53
40	Jim Kelly	BUF	NYG	25	L	30	212	0	0	205	6.6	52
41	Jim Plunkett	RAI	WAS	18	W	25	172	1	0	174	6.4	48
42	Roger Staubach	DAL	DEN	12	W	25	183	1	0	142	4.8	45
43	Brad Johnson	TAM	OAK	37	W	34	215	2	1	210	6.2	45
44	Earl Morrall	BAL	DAL	5	W	15	147	0	1	102	6.8	43
45	Ben Roethlisberger	PIT	ARI	43	W	30	256	1	1	209	6.5	37
46	Bob Griese	MIA	MIN	8	W	7	73	0	0	63	7.9	34
47	Brett Favre	GNB	DEN	32	L	42	256	3	1	240	5.6	34
48	Daryle Lamonica	OAK	GNB	2	L	34	208	2	1	181	4.9	32
49	Fran Tarkenton	MIN	MIA	8	L	28	182	0	1	141	4.5	31
50	Gary Kubiak	DEN	NYG	21	L	4	48	0	0	45	10.2	25
51	Troy Aikman	DAL	BUF	28	W	27	207	0	1	159	5.5	21
52	Tom Brady	NWE	NYG	46	L	41	276	2	1	261	6.1	20
53	Len Dawson	KAN	GNB	1	L	27	211	1	1	135	4.2	19
54	Trent Dilfer	BAL	NYG	35	W	25	153	1	0	154	5.5	17
55	Tom Brady	NWE	STL	36	W	27	145	1	0	154	5.3	14
56	Len Dawson	KAN	MIN	4	W	17	142	1	1	97	4.9	10
57	Gary Kubiak	DEN	SFO	24	L	3	28	0	0	25	6.8	7
58	Frank Reich	BUF	WAS	26	L	1	11	0	0	10	9.4	5
59	Steve Young	SFO	DEN	24	W	3	20	0	0	20	6.5	5
60	Vince Ferragamo	RAM	PIT	14	L	25	212	0	1	127	4.4	4
61	Danny White	DAL	DEN	12	W	2	5	0	0	3	1.1	4
62	Matt Hasselbeck	SEA	PIT	40	L	49	273	1	1	234	4.5	3
63	Ben Roethlisberger	PIT	GNB	45	L	40	263	2	2	211	5.1	2
64	Bill Musgrave	SFO	SDG	29	W	1	6	0	0	6	5.2	0
65	Fran Tarkenton	MIN	OAK	11	L	35	205	1	2	132	3.7	-4
66	Babe Parilli	NYJ	BAL	3	W	1	0	0	0	0	-0.4	-5
67	Zeke Bratkowski	GNB	KAN	1	W	1	0	0	0	-1	-0.8	-5
68	Jay Schroeder	WAS	DEN	22	W	1	0	0	0	-1	-0.6	-6
69	Pete Beathard	KAN	GNB	1	L	5	17	0	0	7	1.3	-6
70	Tony Banks	BAL	NYG	35	W	1	0	0	0	-1	-0.7	-6
71	Eli Manning	NYG	NWE	42	W	34	255	2	1	182	4.9	-8
72	Bob Griese	MIA	WAS	7	W	11	88	1	1	44	3.4	-8
73	Peyton Manning	IND	CHI	41	W	38	247	1	1	184	4.7	-10
74	John Elway	DEN	GNB	32	W	22	123	0	1	98	4.3	-12
75	Don Strock	MIA	WAS	17	L	3	0	0	0	-3	-0.9	-17
76	Steve Fuller	CHI	NWE	20	W	4	0	0	0	-3	-0.6	-23
77	Ron Jaworski	PHI	OAK	15	L	38	291	1	3	146	3.8	-28
78	Joe Theismann	WAS	MIA	17	W	23	143	2	2	74	2.8	-33
79	Dan Marino	MIA	SFO	19	L	50	318	1	2	219	4.1	-33
80	Elvis Grbac	SFO	SDG	29	W	1	0	0	0	-30	-28.2	-36
81	Johnny Unitas	BAL	NYJ	3	L	24	110	0	1	65	2.7	-37
82	David Woodley	MIA	WAS	17	L	14	97	1	1	28	1.9	-37
83	Donovan McNabb	PHI	NWE	39	L	51	357	3	3	249	4.5	-40
84	Norris Weese	DEN	DAL	12	L	10	22	0	0	-18	-1.6	-42
85	Gale Gilbert	SDG	SFO	29	L	6	30	0	1	-17	-2.7	-44
86	Gary Cuozzo	MIN	KAN	4	L	3	16	0	1	-32	-9.6	-46
87	Johnny Unitas	BAL	DAL	5	W	9	88	1	2	-12	-1.3	-47
88	Tom Brady	NWE	NYG	42	L	48	266	1	0	219	4.1	-53
89	Bob Griese	MIA	DAL	6	L	23	134	0	1	30	1.3	-58
90	Boomer Esiason	CIN	SFO	23	L	25	144	0	1	78	2.6	-65
91	Jim Kelly	BUF	DAL	28	L	50	260	0	1	182	3.4	-66
92	Stan Humphries	SDG	SFO	29	L	49	275	1	2	189	3.7	-67
93	Ben Roethlisberger	PIT	SEA	40	W	21	123	0	2	45	2	-67
94	Tony Eason	NWE	CHI	20	L	6	0	0	0	-40	-5.6	-72
95	Roger Staubach	DAL	PIT	10	L	24	204	2	3	37	1.2	-78
96	Chris Chandler	ATL	DEN	33	L	35	219	1	3	91	2.5	-79
97	Joe Kapp	MIN	KAN	4	L	25	183	0	2	39	1.4	-81
98	John Elway	DEN	WAS	22	L	38	257	1	3	93	2.2	-90
99	Rex Grossman	CHI	IND	41	L	28	165	1	2	54	1.9	-90
100	Steve Grogan	NWE	CHI	20	L	30	177	1	2	56	1.6	-105
101	Jim Kelly	BUF	DAL	27	L	7	82	0	2	-72	-9.3	-107
102	Joe Theismann	WAS	RAI	18	L	35	243	0	2	73	1.8	-112
103	Craig Morton	DAL	BAL	5	L	26	127	1	3	-2	-0.1	-112
104	Fran Tarkenton	MIN	PIT	9	L	26	102	0	3	-33	-1.3	-127
105	Earl Morrall	BAL	NYJ	3	L	17	71	0	3	-64	-3.8	-136
106	Frank Reich	BUF	DAL	27	L	31	194	1	2	16	0.5	-137
107	Neil O'Donnell	PIT	DAL	30	L	49	239	1	3	122	2.3	-147
108	Billy Kilmer	WAS	MIA	7	L	28	104	0	3	-48	-1.6	-159
109	Drew Bledsoe	NWE	GNB	31	L	48	253	2	4	74	1.4	-178
110	John Elway	DEN	SFO	24	L	26	108	0	2	-22	-0.7	-182
111	Rich Gannon	OAK	TAM	37	L	44	272	2	5	35	0.7	-212
112	Craig Morton	DEN	DAL	12	L	15	39	0	4	-157	-9	-214
113	Jim Kelly	BUF	WAS	26	L	58	275	2	4	30	0.5	-269
114	Kerry Collins	NYG	BAL	35	L	39	112	0	4	-124	-2.9	-335

If you type Montana’s name into the search box, you can see that he has the 1st, 4th, 11th and 27th best performance in Super Bowl history. The best performance in a losing effort goes to Jake Delhomme, who shredded the Patriots secondary in the second half of Super Bowl XXXVIII (he began the game 1 for 9 for 1 yard). The worst performance in a winning effort, unsurprisingly, goes to Ben Roethlisberger in Super Bowl XL, although Joe Theismann against the Dolphins gets an honorable mention. Worst performance overall goes to Kerry Collins, although Craig Morton’s 4 interceptions and 39 yards on 15 attempts against his former team in Super Bowl XII could give Collins a run for his money.

What about best championship game performances in the pre-Super Bowl era?

Rk	QB	Tm	Opp	Year	W/L	Att	Pyd	TD	INT	CY	CYP	VAL
1	Tobin Rote	DET	CLE	1957	W	19	280	4	0	380	19	304
2	Sid Luckman	CHI	WAS	1943	W	26	286	5	0	386	14.8	248
3	Otto Graham	CLE	RAM	1950	W	33	298	4	1	292	7.7	236
4	Sammy Baugh	WAS	CHI	1937	W	33	335	3	1	320	9.7	228
5	Harry Newman	NYG	CHI	1933	L	19	209	2	1	204	10.7	197
6	Charlie Conerly	NYG	CHI	1956	W	10	195	2	0	232	22.1	192
7	Bart Starr	GNB	NYG	1961	W	17	164	3	0	224	13.2	152
8	Otto Graham	CLE	DET	1954	W	12	163	3	2	193	12.9	135
9	Frank Ryan	CLE	BAL	1964	W	18	206	3	1	212	11.2	132
10	Norm Van Brocklin	RAM	CLE	1951	W	6	128	1	0	148	24.7	129
11	Tobin Rote	SDG	BOS	1963	W	15	173	2	0	226	13.1	127
12	Sid Luckman	CHI	NYG	1941	W	12	160	0	0	160	13.3	125
13	George Blanda	HOU	LAC	1960	W	31	301	3	0	361	11.6	123
14	Charlie Conerly	NYG	BAL	1958	W	14	187	1	0	190	11.6	122
15	Arnie Herber	GNB	NYG	1938	L	14	123	1	0	143	10.2	117
16	Johnny Unitas	BAL	NYG	1959	W	29	264	2	0	267	7.4	115
17	Charlie O'Rourke	CHI	WAS	1942	L	7	128	0	0	128	18.3	105

[continue reading…]

References[+]

References
↑1	Note that I do not have individual playoff sack data prior to 2008, so I am using pro-rated sack numbers based on team sack data.

Tagged as: GQBOAT, Joe Montana, Kurt Warner, Peyton Manning, Playoffs, Tom Brady

{ 8 comments }

The Greatest QB of All-Time IV, Part II: Career Rankings

by Chase Stuart on August 30, 2012

in G.O.A.T., History, Passing, Statistics

Yesterday, I explained the methodology behind the formula involved in ranking every quarterback season in football history. Today, I’m going to present the career results. Converting season value to career value isn’t as simple as it might seem. Generally, we don’t want a player who was very good for 12 years to rank ahead of a quarterback who was elite for ten. Additionally, we don’t want to give significant penalties to players who struggled as rookies or hung around too long; we’re mostly concerned with the peak value of the player.

What I’ve historically done — and done here — is to give each quarterback 100% of his value or score from his best season, 95% of his score in his second best season, 90% of his score in his third best season, and so on. This rewards quarterbacks who played really well for a long time and doesn’t kill players with really poor rookie years or seasons late in their career. It also helps to prevent the quarterbacks who were compilers from dominating the top of the list. The table below shows the top 150 regular season QBs in NFL history using that formula, along with the first and last years of their careers, their number of career attempts (including sacks and rushing touchdowns), and their career records and winning percentages (each since 1950). For visibility reasons, I’ve shown the top 30 quarterbacks below, but you can change that number in the filter or click on the right arrow to see the remaining quarterbacks.
[continue reading…]

Tagged as: Brett Favre, Dan Marino, GQBOAT, John Elway, Johnny Unitas, Peyton Manning, quarterbacks, Tom Brady

{ 21 comments }

The Greatest QB of All-Time IV, Part I (Methodology)

by Chase Stuart on August 29, 2012

in G.O.A.T., History, Passing, Statistics

In 2006, I took a stab at ranking every quarterback in NFL history. Two years later, I acquired more data and made enough improvements to merit publishing an updated and more accurate list of the best quarterbacks the league has ever seen. In 2009, I tweaked the formula again, and published a set of career rankings, along with a set of strength of schedule, era and weather adjustments, and finally career rankings which include those adjustments and playoff performances.

If nothing else, that was three years ago, so the series was due for an update. I’ve also acquired more data, enabling me to tweak the formula to better reflect player performance. But let’s start today with an explanation of the methodology I’m using. To rank a group of players, you need to decide which metric you’re ordering the list by. I’ll get to all of the criteria I’m not using in a little bit, but the formula does use each of the following: pass attempts, passing touchdowns, passing yards, interceptions, sacks, sack yards lost, fumbles, fumbles recovered, rush attempts, rushing yards and rushing touchdowns. Most importantly, the formula is adjusted for era and league.

Two of the best quarterbacks ever.

So where do we begin? We start with plain old yards per attempt. I then incorporate sack data by removing sack yards from the numerator and adding sacks to the denominator . To include touchdowns and pass attempts, I gave a quarterback 20 yards for each passing touchdown and subtracted 45 yards for each interception. This calculation — (Pass Yards + 20 * PTD – 45 * INT – Sack Yards Lost) / (Sacks + Pass Attempts) forms the basis for Adjusted Net Yards per Attempt, one of the key metrics I use to evaluate quarterbacks.

For purposes of this study, I did some further tweaking. I’m including rushing touchdowns, because our goal is to measure quarterbacks as players. There’s no reason to separate rushing and passing touchdowns from a value standpoint, so all passing and rushing touchdowns are worth 20 yards and are calculated in the numerator of Adjusted Net Yards per Attempt. To be consistent, I also include rushing touchdowns in the denominator of the equation. This won’t change anything for most quarterbacks, but feels right to me. A touchdown is a touchdown.
[continue reading…]

References[+]

References
↑1	I have individual sack data for every quarterback since 1969. For seasons before then, I have team sack data going back to 1949. For seasons before 1950, I ignored sacks; for seasons between 1950 and 1969, I gave each quarterback an approximate number of sacks, giving him the pro-rated portion of sacks allowed by the percentage of pass attempts he threw for the team. While imperfect, I thought this “fix” to be better than to ignore the data completely, especially for years where one quarterback was responsible for the vast majority of his team’s pass attempts.

Tagged as: Aaron Rodgers, Dan Marino, Eli Manning, GQBOAT, Joe Montana, Johnny Unitas, Peyton Manning, quarterbacks, Steve Young, Tom Brady

{ 13 comments }

Russell Wilson continues the NFL’s rookie movement at quarterback

by Chase Stuart on August 27, 2012

in Passing, Rookies

This is a starting NFL quarterback in an NFL uniform. Welcome to 2012.

Andrew Luck and Robert Griffin III were drafted as franchise saviors, and have been expected to start on opening day for months; more recently Brandon Weeden in Cleveland and Ryan Tannehill in Miami won starting jobs. Then, last night, Pete Carroll announced that Russell Wilson had beaten Matt Flynn in the Seahawks quarterback battle. Barring injury, we’ll see five rookie quarterbacks starting on opening day for the first time since 1950 (and likely ever). Before Wilson, we were already in record territory, as no more than three teams have ever started the season with rookie quarterbacks since 1950 (and likely ever). In 1969, Roger Staubach, Greg Cook and James Harris were week one starters for the Cowboys, Bengals and Bills. The year before, Greg Landry, Dewey Warren, and Dan Darragh started for the Lions… Bengals and Bills. And in the AFL’s inaugural season, three teams fielded rookie quarterbacks. But on average, less than one rookie quarterback has started a team’s opening game each season since the merger.

Last year, Cam Newton and Andy Dalton were opening day starters, and their success (along with the success of Joe Flacco and Matt Ryan) have undoubtedly made teams become more willing to start rookie quarterbacks. In fact, the youth movement goes beyond just this year’s class: in addition to Newton and Dalton, Jake Locker, Christian Ponder, and Blaine Gabbert will be second-year quarterbacks starting in week one this season. That’s another record, breaking the seven such quarterbacks in 2000. Remember 1999, the Year of the Quarterback in the NFL Draft? Tim Couch, Donovan McNabb, Akili Smith, Cade McNown, and Daunte Culpepper were all high first-round draft picks, and all were sophomore starters in 2000. Shaun King, fresh off a strong late-season run for Tampa Bay, joined the group in week 1 of the 2000, as did Jeff Garcia in San Francisco.

What’s the explanation? Luck, Griffin, and Newton were uber elite talents who were too good to sit. Wilson legitimately won the Seahawks job in training camp and preseason, a rare event in any era for a rookie quarterback. But the rest of the group — Weeden, Tannehill, Dalton, Gabbert, Ponder, and Locker — seem to signal a shift in NFL philosophy. The table below lists all quarterbacks drafted in the top 40 — but not in the top 5 — since 1970, and the first year in their career when they started for their team in week one:
[continue reading…]

Tagged as: Browns, Colts, Dolphins, Redskins, Seahawks

{ 2 comments }

Super Bowl champions and how they passed, ran and played defense

by Chase Stuart on August 21, 2012

in Defense, History, Passing, Rushing

I broke down each of the NFL and AFL champions since 1950 into three categories:

Pass Efficiency, measured by a modified version of ANY/A. The formula was (Passing Yards + 10*TD – 22.5*INT – Sack Yards)/(Pass Attempts + Sacks). This strikes a middle ground between traditional ANY/A and NY/A.
Rushing Success, according to the following formula: (Rushing Yards + 10*RTD + 5*Rushing1stDowns)/(Carries).
Defensive Rating, based on the number of offensive touchdowns scored by their opponents.

There are ways to quibble with those categories, and I won’t begrudge anyone who does. After giving each team a rating in each category, I calculated how they compared to the league average in each season. In all cases, the average is 100%, and a number higher than 100% means better.

Here’s what each of the columns mean, from left to right. In 2011, the New York Giants won the Super Bowl; they allowed 43 touchdowns to opposing offenses, averaged 7.6 in my modified version of ANY/A, and averaged 4.9 adjusted yards per carry. The next three columns show how New York ranked relative to league average. By allowing 43 scores, the Giants D was well below average, putting them at 83% of the average mark; they were 25% better than average at passing, but only 86% of league average efficiency in the running game. Since the Giants highest rating came in the passing category, they are listed in the Identity column as a Passing team.
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Tagged as: Super Bowl

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