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

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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.
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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.

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 ^[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 … Continue reading. 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.
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Bill Simmons wrote about LaDainian Tomlinson last month and called him the best fantasy football player of all-time. “Greatest ever” debates are always subjective, but at least when it comes to fantasy football, we can get pretty close to declaring a definitive answer. Joe Bryant’s landmark “Value Base Drafting” system explained that the “value of a player is determined not by the number of points he scores, but by how much he outscores his peers at his particular position.” Bryant came up with the concept of calculating a ‘VBD’ number for each player to measure their value.

A player’s VBD is easy to calculate. Each player’s VBD score is the difference between the amount of fantasy points he scored and the fantasy points scored by the worst starter (at his position) in your fantasy league. A player who scores fewer fantasy points than the worst starter has a VBD of 0. There is no standard scoring system for fantasy leagues, so a player’s fantasy points total will depend on the specific league’s scoring rules. ^[1]I’ve decided to use a blend of the most common scoring options: 1 point per 20 yards passing, 5 points per passing touchdown, -2 points per interception, 6 points for rushing/receiving … Continue reading And, of course, his VBD score will change depending on the number of starters at each position in the league. ^[2]Again, I’m using a blend here, but for baseline purposes I’m using QB12, RB24, WR32 and TE12, since the standard 12-team league starts 1 QB, 2 RBs, 2-3 WRs and 1 TE.

That said, once you pick a scoring system and a set of rules, it’s easy to calculate career VBD scores for every player since 1950 ^[3]I’ve pro-rated production for those players who were part of seasons when the NFL did not have a 16-game schedule; I also changed the baseline numbers depending on the number of teams in the … Continue reading. Let’s start with the quarterbacks:

Player	Years	POS	Teams	VBD	OVR RK	POS RK
Peyton Manning	1998--2010	QB	clt	1071	9	1
Brett Favre	1992--2010	QB	atl-gnb-nyj-min	1061	10	2
Dan Marino	1983--1999	QB	mia	988	14	3
Fran Tarkenton	1961--1978	QB	min-nyg	921	15	4
Steve Young	1985--1999	QB	tam-sfo	774	24	5
Joe Montana	1979--1994	QB	sfo-kan	727	33	6
Randall Cunningham	1985--2001	QB	phi-min-dal-rav	723	35	7
Tom Brady	2000--2011	QB	nwe	720	36	8
Drew Brees	2001--2011	QB	sdg-nor	688	38	9
John Elway	1983--1998	QB	den	660	40	10
Roger Staubach	1969--1979	QB	dal	630	44	11
Johnny Unitas	1956--1973	QB	clt-sdg	625	47	12
Warren Moon	1984--2000	QB	oti-min-sea-kan	592	57	13
Ken Anderson	1971--1986	QB	cin	539	74	14
Sonny Jurgensen	1957--1974	QB	phi-was	528	77	15
Dan Fouts	1973--1987	QB	sdg	526	78	16
Daunte Culpepper	1999--2009	QB	min-mia-rai-det	515	80	17
Aaron Rodgers	2005--2011	QB	gnb	507	83	18
Tobin Rote	1950--1964	QB	gnb-det-sdg-den	494	88	19
Roman Gabriel	1962--1977	QB	ram-phi	404	130	20
Rich Gannon	1988--2004	QB	min-was-kan-rai	396	135	21
Kurt Warner	1998--2009	QB	ram-nyg-crd	396	136	22
Bobby Layne	1950--1962	QB	chi-nyy-det-pit	385	140	23
Y.A. Tittle	1950--1964	QB	bcl-sfo-nyg	384	141	24
Daryle Lamonica	1963--1973	QB	buf-rai	368	153	25

[continue reading…]

Darren McFadden has missed games due to injury in each of his four seasons in the NFL. But he earns the label “injury prone” instead of “bust” thanks to his incredible production the past two years. In 2010 and 2011, McFadden totaled 2,432 yards from scrimmage and 15 touchdowns in 20 games while averaging 5.3 yards per carry and 10.0 yards per reception.

But is the injury prone label fair? From a rearview standpoint, it certainly is. But the label carries with it the perception that he will continue to be injury prone. Is that fair?

From a statistical standpoint, we’re really limited by sample size. In the past two decades, only a handful of young running backs have been as productive as McFadden despite dealing with significant injury issues. Ricky Williams played in 12 and 10 games his first two seasons, and earned the injury prone label before three straight 16-game seasons. Steven Jackson missed games here and there early in his career, and in fact still has just two 16-game seasons in his career. But Jackson is no longer considered injury prone and has also registered three 15-game seasons.

Fred Taylor resided for years at the intersection of talented and injury prone, earning colorful nicknames like ‘Fragile Fred’ and ‘Fraud Taylor.” He played in only 40 games in his first four seasons, but still scored 37 touchdowns, averaged 4.7 yards per carry, and averaged 106 yards from scrimmage per game. He would play in 16 games each of the next two seasons, before missing games due to injury every other season for the rest of his career.

Cadillac Williams played in 14 games in each of his first two seasons, and things only got worse from there. He played in just 10 games the next two seasons, before playing in 16 games in both 2009 and 2010. Julius Jones missed significant time in each of his first two seasons, but then played in 16 games in each of his next two years. On the other hand, Kevin Jones’s career went 15-13-12-13-11 in terms of games played. Robert Smith was a track star on the gridiron and often seemed as tough as one. In his first two seasons as the starter with the Vikings, he wound up being inactive half of the time each year. In 1997 and 1998, he played in 14 games, but Smith would only play one 16-game season in the NFL: his last one.

But back to McFadden. Let’s start with some baseline about what the anti-McFadden would look like. From 1990 to 2010, there were 91 ^[1]This excludes Robert Edwards, Jamal Lewis and Terry Allen, each of whom would suffered a season-ending injury prior to the start of the following season. running backs, age 25 or younger, who rushed for at least 1,000 yards and played in 16 games. Only 38 of those 91 running backs (42%) played in 16 games the next season, while the group averaged 13.9 games played in the following year. The median was 15 games played, with 58% of running backs playing in 15 or 16 games.
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Twice in four years, the Buffalo Bills have teased their fans. In 2008, the Bills started 5-1, and Peter King named Trent Edwards his MVP after the first quarter of the season. Edwards had led fourth-quarter comebacks and game-winning drives in the second and third weeks of the year, and he ranked in the top-five in AY/A after seven weeks.

The former Stanford Cardinal would rank 24th in AY/A the rest of the season while Buffalo finished the year with a 2-8 record.

The Bills won just ten games the next two seasons, but made some noise at the start of the 2011 season. Going back to the nerd well at quarterback, Buffalo raced out to a 5-2 start. Fitzpatrick led two fourth-quarter comebacks/game-winning drives and ranked 11th in AY/A after eight weeks. Unfortunately, the former Harvard star ranked 32nd in that metric over the last nine weeks of the season, and the Bills finished the season 1-8.

How unusual is it for a team to have such a hot start and cold finish? It’s simple enough to look at first-half/second-half splits, but I prefer a more nuanced approach by weighing each team game based on when it occurred; e.g., game 1 counts 16 times as much as game 16, game 2 counts 15 times as much as game 16, game 3 counts 14 times as much as game 16, and so on. I looked at each team since 1990 and calculated their actual winning percentage and their “weighted” winning percentage.

The 2011 Bills had a 0.375 winning percentage last year, but by placing greater weight on games earlier in the season, Buffalo had a 0.507 weighted winning percentage. In 2008, the Bills had a 0.438 actual winning percentage and a 0.566 weighted winning percentage. As it turns out, those were two of the five “strongest-starting” teams of the last five years. The table below lists the “strongest-starting teams” since 1990, along with their actual and weighted winning percentages. The last column represents the difference between the two winning percentages.
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Last year, I noted that Drew Brees had thrown a touchdown in 37 consecutive games and examined his chances of breaking the NFL record. The current mark is held by Johnny Unitas, who threw a touchdown in 47 consecutive games from 1956 to 1960. By the end of the 2011 season, Brees had upped his streak to 43 games, which positions Brees to break the record in week 5 of this season, against his former team, the San Diego Chargers, on Sunday Night Football.

Assuming Brees breaks the record, we can expect a four-hour telecast devoted to the greatness of Drew Brees, which is largely warranted. Brees is a future Hall of Famer and one of the most accurate quarterbacks in the history of the game. And he’ll be breaking one of the oldest records in football, one currently held by the standard bearer at the position.

If you’ve been at Football Perspective for long, you probably know where this is going. How impressive will it be for Brees to break this record? The short answer is, probably not as impressive as you might think.

What are the odds of throwing a touchdown in 47 straight games ^[1]Assuming independence and a consistent rate per game? Brees deserves all of the credit and praise he gets for being an elite quarterback, and a Blaine Gabbert-type is obviously not going to be the one to break this record. But the real question we want to ask is what are the odds of a star quarterback throwing a touchdown in 47 consecutive games. We can get a pretty good estimate of that.

In 44 games from 2002 to 2005, Marc Bulger threw a touchdown in 93% of his games, or 41 of 44 games. And in two of the games where he did not throw a touchdown, he threw fewer than five passes. In 73 games from 2000 to 2004, Daunte Culpepper threw a touchdown in 86% of his games. Brett Favre, from 2001 to 2004, threw a touchdown in 95% of his games. Eli Manning, from 2005 to 2011, threw a touchdown in 86% of his starts and was booed by Giants fans in just as many. Peyton Manning, excluding his rookie year, threw a touchdown in 87% of his games with the Colts. Philip Rivers once threw a touchdown in 50 of 54 straight games. Aaron Rodgers has thrown a touchdown in 50 of his last 53 games, with one of his zeroes coming in a partial game against the Lions. Tony Romo has thrown a touchdown in 90% of his games since 2007, and 92% of those games if you exclude two games he did not finish. Matt Ryan has thrown a touchdown in 30 of his last 31 games. Matthew Stafford has thrown a touchdown in 28 of his last 30 games, with one of his shutouts coming in a game he did not finish due to injury. From ’99 to ’01, Kurt Warner threw a touchdown in 93% of his games.

And then there’s Tom Brady. Since 2007, Brady has thrown a touchdown in 92% of his starts, or 94% if you exclude his game against the Chiefs when he tore his ACL in the first quarter. Brady has also thrown a touchdown in each regular season game the past two seasons, which means he could also break Unitas’ mark in 2012.

There is obviously an upper limit to the question ‘what is the likelihood of an elite quarterback playing at an elite level throwing a touchdown in any given game?’ Last year, I speculated that Brees’ likelihood was around 89-91%, which in retrospect, might be a little low. The upper limit is probably closer to 96 or 97%, although obviously very few quarterbacks could get there. If we assume complete games — i.e., that the quarterback won’t get injured or get benched or rested — maybe a star quarterback in today’s game has a 94% chance of throwing a touchdown in any given game.

In that case, such a quarterback has a 5% chance of throwing a touchdown in 48 consecutive games. In some ways, of course, this is a “what are the odds of that” sort of question. Yes, Brees is at 43 in a row, but he’s not alone. Brady has thrown a touchdown in every game the last two seasons. Stafford has done it in 18 straight games, Rodgers for 17, and Ryan is at 15. And, of course, players like Kurt Warner and Brett Favre and Peyton Manning have played at elite levels for stretches just like Brees.

Perhaps the better question is, assuming 14 elite quarterbacks playing at elite levels play in 48 straight games, and each has a 94% chance of throwing a touchdown in any given game, what are the odds that none of them go 48/48? The answer to that: 48%. In other words, it is more likely than not that some quarterback would break the record.

Brees deserves all the praise in the world for essentially putting himself at the upper limit of elite quarterback play. He deserves credit for having a quick release and excelling at pre-snap coverage, which limits the amount of hits he takes. On the other hand, he’s fortunate to have almost entirely avoided playing in poor weather. He’s fortunate to have avoided injury on the hits he has taken, and to have not played for a coach that chose to bench him for a meaningless game after a drive or two (in fact, he missed week 17 of the 2009 season entirely, keeping his streak alive). He’s also fortunate that he’s thrown a touchdown in 43 games and not 41 or 42 out of 43, like many other elite quarterbacks. Brees has had bad games during this streak — in 7 of them, he’s averaged 4.8 AY/A or fewer — but he always managed to throw at least one touchdown. That’s less skill than luck, and you can read about some of Brees’ near misses here.

The skill involved for Brees is getting himself to that upper limit. Given enough quarterbacks playing at elite levels for enough years, Unitas’ record was bound to fall. Brees happens to be one of those quarterbacks.

In 1983, the Washington Redskins set an NFL record by scoring 541 points. Fifteen years later, the Minnesota Vikings broke that mark by going 15-1 and scoring 556 points. Then, in 2007, the New England Patriots topped Minnesota by going undefeated and scoring 589 points, the most in NFL history.

Last year’s Green Bay Packers scored 560 points, preventing Randy Moss from being a star on the two highest scoring teams in NFL history. But it’s not the Patriots, Vikings or Redskins that hold the mark for most points scored per game in NFL history. New England averaged 36.8 points per game in 2007, but one NFL team in the pre-modern era scored 38.83 points per game.

They’re the subject of today’s trivia question. Can you name the highest scoring team in NFL history?

The 2011 Giants were one of the more confusing teams in recent memory. Will this year’s the Giants play like the defending Super Bowl champions or the team that allowed more points than they scored last season? Jason Lisk points out that there’s a third option, and we should consider the 2011 Giants as a 13-7 team that faced an extremely difficult schedule.

Let’s start by recognizing that the 2011 Giants faced a difficult schedule in the regular season; not only was the NFC East competitive, but New York also faced the top four teams in the NFL outside of their division. In 2011, the Giants ranked 13th in the Simple Rating System. For the uninitiated, the SRS is a predictive system, which means it could theoretically place a 3-5 team ahead of a 7-1 team. The SRS mimics the points spread you would see in Las Vegas rather than a power ranking system. As the name implies, it’s simple in the sense that it only looks at two variables: strength of schedule and margin of victory. Each game is given equal weight. A win by 10 points over a team that is 5 points below average is equal to a 5-point win over an average team. The SRS is always just the sum of the margin of victory and the opponent’s rating. Unlike many systems, in the SRS, the values have meaning. A team with an SRS rating of +6.0 means that team is six points better than average.

It’s complicated to create these ratings, but I’ve done the heavy lifting ^[1]The tricky part is that each team’s strength of schedule is dependent on the ratings of each of their opponents, which is dependent on the ratings of each of their opponents, which includes the … Continue reading. Here were the SRS ratings for each team immediately after week 17 last season:

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Yesterday, I looked at how frequently the highest drafted rookie running back ended leading his draft class in rushing yards. Today, we’ll examine how often the best rookie running back ends up being having the most career rushing yards among the members from his class.

I performed this same exercise at wide receiver, and concluded that as great as A.J. Green was last season, the odds were stacked against him leading the 2011 rookie receiver class in career receiving yards. ^[1]From 1978 to 2008, only three of the 31 wide receivers with the best rookie seasons ended up with the most receiving yards from their class. For whatever reason, there simply is not a strong correlation between rookie performance and career performance for wide receivers. Is the same true at the running back position?

There was an eleven-year stretch from ’92 to ’02, when Ricky Watters, Jerome Bettis, Marshall Faulk, Curtis Martin, Eddie George, Corey Dillon, Fred Taylor, Edgerrin James, LaDainian Tomlinson, and Clinton Portis each led their class in rushing yards both as rookies and over the course of their careers. The lone exception came in 2000, when Mike Anderson nudged by Jamal Lewis to lead the ’00 class in rookie rushing yards, while Lewis ended with the most career rushing yards. If I had written this article a decade ago, I would have thought that unlike at the receiver position, there was an extremely strong correlation between rookie and career performance for the top running backs.

But since then, things have changed. Domanick Williams (Larry Johnson), Kevin Jones (Steven Jackson), Cadillac Williams (Frank Gore), Joseph Addai (Maurice Jones-Drew), Steve Slaton (Chris Johnson), and Knowshon Moreno (Arian Foster) led all rookies in rushing yards but have been passed in the career category by another back from the same rookie class. It’s too early to get a handle on the last two draft classes, although I certainly wouldn’t take even odds on either Ben Tate or LeGarrette Blount finishing with the most career rushing yards of any running back who entered the league in either 2010 or 2011.

The table below shows the top rookie running backs and the top career running backs from each class since 1978.
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Measuring team age in the N.F.L. is tricky. Calculating the average age of a 53-man roster is misleading because the age of a team’s starters is much more relevant than the age of a team’s reserves. The average age of a team’s starting lineup isn’t perfect, either. The age of the quarterback and key offensive and defensive players should count for more than the age of a less relevant starter. Ideally, you would want to calculate a team’s average age by placing greater weight on the team’s most relevant players.

That’s not easy to do for the 2012 season, but we can apply one method to last year’s rosters. Using Pro-Football-Reference’s Approximate Value system, it’s simple to calculate the weighted age of every team last season, by weighing each player’s age proportionately to his percentage of contribution (as measured by the Approximate Value system) to his team.

Let’s take a look at the (weighted) average age of each offense last season:

Offense

It’s not too surprising to see Seattle at the youngest team in the league last year, and they look to have a young offense again in 2012. The Seahawks will get younger at quarterback if either Matt Flynn or Russell Wilson replaces Tarvaris Jackson. At wide receiver, Sidney Rice (26 in 2012), Doug Baldwin (24) and Golden Tate (24) are the projected top three, although the team just added 29-year-old Braylon Edwards. Marshawn Lynch is still just 26, and the Seahawks added Utah State’s Robert Turbin in April’s draft. The offense line, anchored around LT Russell Okung (25) and C Max Unger (26), has all five starters under the age of 30, as are both Zach Miller and Kellen Winslow, Jr..

The Patriots, meanwhile, featured the league’s oldest offense last season. We all know about Tom Brady (34 in 2011) and Wes Welker (30), but Brian Waters (35), Matt Light (34), Logan Mankins (29), and Deion Branch (32) made were older members of the Patriots’ supporting cast. New England has a pair of young tight ends (Rob Gronkowski, Aaron Hernandez) and young running backs (Stevan Ridley, Shane Vereen), but the rest of the offense remains old. Obviously Brady and Welker continue to play at a high level, but the team didn’t wasn’t focused on age when it added wide receiver Brandon Lloyd (32).
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[Note: I’m scheduled to appear on The Bobby Curran Show on ESPN 1420 at just after 2:00 today. If you’re interested, you can listen here.]

Rex Ryan is the Tim Tebow of coaches: whatever he says tends to get magnified. I was sitting a few feet from Ryan when he made his latest controversial comment. Keyshawn Johnson asked Ryan if having a former head coach in Tony Sparano now coaching the offense would allow him to focus more on the defense. Ryan said it would, although Ryan previously vowed to also be more involved with the offense. The next question asked about Ryan’s confidence, and he said he had a lot of confidence in himself and his coaching staff. He went on:

Now, I wasn’t even in the defensive meeting last night, but I have complete faith and trust in the coaches we have. As I said, it’s easy for me to say I’m the best defensive coach in football. Now that’s saying something, because Dick LeBeau’s pretty (darn) good, Bill Belichick is pretty good. But that’s the way I’ve always believed. And you know what, I believe it because of the guys I coach with, there’s no doubt about that, and the guys that I’ve coached. That’s the truth, and that’s how I feel. I’m going to be more involved over there, calling games or whatever. Obviously, Mike Pettine, that’s my right hand guy, he’s always been my right hand guy and that’s the way it’s always going to be.

Not that inflammatory, is it? In any event, Ryan also issued a call to the media on Saturday, and if you’ve ever read this blog, you know he got my attention with what he said:

I’m still waiting to see somebody put the stats up there, because I know I’m crazy, but go ahead and just put them out there one day, since I’ve been a coordinator and head coach, I dunno where I’d rank…I really don’t even know the answer…Now watch Dick LeBeau get me.

Well, Rex, I’ll put the stats out there for you. Presumably we want to compare Ryan to all current head coaches (with defensive backgrounds) and defensive coordinators in the league. There are only 25 defensive coordinators to examine, as sevens teams do not have coordinators with any relevant track record. Both Missouri teams are actually without defensive coordinators this year: In Kansas City, Romeo Crennel will be head coach and defensive coordinator, while in St. Louis, the Rams are going with a committee approach to replace the suspended Gregg Williams. In addition, five men will be first-time defensive coordinators in 2012: Matt Patricia in New England, Kevin Coyle in Miami, Alan Williams in Minnesota, Jason Tarver in Oakland and John Pagano in San Diego.
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Bill Barnwell wrote an interesting article where he tried to identify the best running back in football. His article made me wonder: which player will gain the most rushing yards over the next decade?

It probably makes sense to start with a look at history. I suspect you would have been able to guess that LaDainian Tomlinson had the most rushing yards from 2002 to 2011, but what about from 1982 to 1991? Or from 1960 to 1969? The table below shows each leader in rushing yards for every ten year period, along with their age and NFL experience during their first season during the relevant period.

Tomlinson entered the league in 2001, but he was so productive in his first nine years that he also led the league in rushing yards gained from 2000 to 2009. O.J. Simpson, Eric Dickerson and Barry Sanders each led the league in rushing yards for ten year periods … when they spent the first three seasons of those decades playing college ball. Jim Brown was even more impressive, as he led the NFL in rushing yards from 1953 to 1962, even though he was just 17 years old in 1953 and did not enter the league until 1957.

But Steve Van Buren has them all beat: he entered the league in 1944, but led all players in rushing from 1938 to 1947. As you may recall, he’s still the Eagles franchise leader in rushing touchdowns. We can also look at the leaders over the last nine seasons, although obviously the ten-year windows are not closed in these cases:

So what can we make of the results? The average running back was just a hair under 22 at the start of his ten year period. Nearly half of all running backs were not yet in the NFL at the start of their ten year run, although that is likely to change now. Those players were in other football leagues, serving their country, or in college, but all three of those factors are less prevalent now. Star running backs leave college a year or two earlier than they did a generation ago, which will make it slightly less likely that a player will not be in the NFL at the start of the next ten-year run.

Fourteen players were rookies at the start of their great stretch, and another 10 were second year players, making nearly 80% of the players having just one year or less of experience in the summer before the start of their streak. What does that mean for the stretch from 2012 to 2021? Trent Richardson is the ideal candidate, as the new Browns running back just turned 21. Last year’s Alabama running sensation, Mark Ingram, was 22 in 2011, while Dion Lewis and Jacquizz Rodgers were the top 21-year-old running backs last season.

No running back started his 10-year stretch atop the leaderboard at the age of 26, and only Hall of Famers Steve Van Buren, Joe Perry, Jim Brown, Walter Payton, Eric Dickerson and Emmitt Smith were 25 at the start of a streak. That makes it pretty easy to rule out Maurice Jones-Drew, Matt Forte, Adrian Peterson and Chris Johnson, all of whom will be 27 in 2012. Ray Rice (25 in 2012), Arian Foster (26), Marshawn Lynch (26) and Ryan Mathews (25) are probably suckers’ bets, too.

LeSean McCoy, Beanie Wells and DeMarco Murray all are entering their age 24 season, making them perhaps the best hope among the young runners with NFL experience. On the other hand, along with Richardson, Doug Martin, David Wilson, Ronnie Hillman and Lamar Miller made the 2012 draft strong at the position. In the NFC West, Isaiah Pead and Kendall Hunter (or LaMichael James) could be the future for their teams for the next decade. As always, it’s too early to say.

In the collegiate ranks, South Carolina’s Marcus Lattimore is expected to be the cream of the 2013 class, with Auburn transfer Michael Dyer and Wisconsin’s Montee Ball also in the mix. And based on past history, we can’t count out sophomores Malcolm Brown or De’Anthony Thomas. If you had to pick which player will lead the league in rushing yards from 2012 to 2021, Trent Richardson is the obvious choice. After him, I’d probably be pretty evenly split among McCoy, Martin and Lattimore.

[After spending the weekend with Doug Drinen, founder of Pro-Football-Reference.com, we decided that Football Perspective needed to revive this fantastic post of his, explaining why “What are the odds of that?” is a much less straightforward question than you might think.]

You may have heard that last month, a roulette wheel at the Rio in Las Vegas landed on the number 19 an incredible seven consecutive times. What are the odds of that?

That may sound like a simple question, but it isn’t. Some would answer the question by stating that the odds of a roulette wheel landing on the number 19 on seven consecutive spins is a simple math problem. There are 38 numbered pockets on an American roulette wheel, so the odds of a ball landing on 19 in one spin of the wheel would be 1 in 38. The odds of that happening seven straight times would simply be (1/38)^7, or 1 in 114 billion. ^[1]I am blurring, and will continue to blur, the distinction between odds and probability. Nothing bad will happen as a result.

An equally plausible response would be that we don’t care that the wheel landed on “19” in seven straight spins, but rather that it landed on the same number for seven straight spins. In that case, what we really want to know is the likelihood that the wheel lands on any number (odds: 38/38, or 100%) and then lands on that same number again on the next six spins (odds: (1/38)^6). The odds of that happening are 1 in 3 billion.

But it’s not that simple, either. The question “What are the odds of that?” can, and often should, be interpreted differently. What are the odds of a roulette wheel, on seven consecutive spins, landing in the following order: 10-34-3-9-18-30-21. Take a second and think about that.

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No, this article isn’t an article about quarterbacks squaring off against ancient Greek mathematicians. Today, we’re going to look at quarterback win-loss records and see how they compare to their Pythagorean win-loss records.

Over 30 years ago, Bill James wrote that, on average, baseball teams’ true strengths could be measured more accurately by looking at runs scored and runs allowed than by looking at wins and losses. Since then, sports statisticians have applied the same thinking to all sports. The formula to calculate a team’s Pythagorean winning percentage is always some variation of:

(Points Scored^2) / (Points Scored ^2 + Points Allowed^2)

With the exponent changing from 2 to whatever number best fits the data for the particular sport. In football, that number is 2.53. We can look, for example, at the Pythagorean records for each team in the league last season, and line it up against their actual record:

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One of my law school professors was very quirky, even by law school professor standards. His preferred examination method was multiple choice, but with a twist. After grading each exam, he would then divide the students into quarters based on their test score. He would then re-examine each question, and measure how the top quarter of students performed on each question relative to the bottom quarter. Any question that more bottom-quarter students answered correctly than top-quarter students would be thrown out, and the exam would be re-graded. As he delicately put out, ‘if the wrong students are getting the question right, and the right students are getting the question wrong, it’s a bad question.’

NFL passing records are falling for a variety of reasons these days, including rules changes and league policies that make the passing game more effective. But there’s another reason: for the first time in awhile, the right people are throwing the most passes in the league. And there’s no better example of that than Drew Brees. Since coming to the Saints in 2006, he’s ranked 1st or 2nd in pass attempts four times, and ranked in the top three in net yards per attempt four times. But even since ’06, we’ve seen the passing game evolve, as the best quarterbacks are now the most likely ones to finish near the top of the leaderboard in pass attempts. In 2010, Peyton Manning had his first 600-attempt season… when he threw 679 passes for the Colts. Tom Brady threw 611 passes last year for the 13-3 Patriots, making New England one of just three teams to threw 600 pass attempts and win 13 or more games in a season. The other two teams? The ’09 Colts and the ’11 Saints.

At various points in the history of the NFL, passing was viewed as an alternative to running, and the high-attempt game was the province of the trailing team. But times are changing in the NFL. I calculated each team’s net yards per attempt (NY/A) and total pass attempts (attempts plus sacks) for every year since 1970. Then, I measured the correlation coefficient between NY/A and pass attempts for the league for each of the last 42 seasons. The chart below shows the correlation coefficient between those two variables (NY/A and pass attempts) for the league as a whole for each year since the merger:
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Thirty years ago, the NFL began officially recording defensive player sacks. Prior to 1982, all teams kept their own individual sack data, but those records (with few exceptions) have never been verified. As a result, it’s an unfortunate reality that for much of NFL history, we simply do not have reliable sack data for individual defensive players.

Three times, Deacon Jones produced 20+ unofficial sacks in the 1960s. ^[1]According to research done by John Turney. In 1967, Raiders defensive end Ben Davidson Ike Lassiter had 17 sacks ^[2]Source. in the AFL. Jack Youngblood and Jim Katcavage both led the league in sacks on two different occasions in the pre-1982 era. ^[3]Source: Turney/Webster Cincinnati Bengal Coy Bacon has been credited with 21.5 unofficial sacks during in 1976. The first team to record 60 sacks in a season was the ’57 Bears, and we can be sure that Doug Atkins recorded more than his fair share of that number. For players like Gino Marchetti, Norm Willey, and Len Ford, even unofficial records weren’t kept during their time, leaving us unsure as to who is the true sack king.

It’s important to remember that just because we don’t have official sack data before 1982 doesn’t mean there were great sack artists before then. But that’s a topic for another today. So while we can’t precisely measure how the forefathers of the game played, we do have official data for the last 30 years. So who has been the best pass rusher of the last three decades?

Using total sacks isn’t a fair method to current players, or to those players who chose to retire instead of sticking around to compile six-sack seasons. So if we want to measure sack dominance, we can’t simply look at total sacks any more than we can grade running backs by looking at career rushing yards. One method I like that I’ve used before is sacks over one-half sack per game. This makes 8 sacks in a 16-game season the bar; a player only gets credit for their production over that level. This means that 12 sacks in a 16-game season brings a value of +4.00, while 16 sacks is twice as valuable at +8.00.There’s no great reason to choose 8 over 6 or 10 or any other number. I chose 8 because it feels right, but I don’t claim that it’s based on anything other than my personal, subjective preference.

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[You can find lots of websites previewing each team as we head towards the 2012 season. You won’t find that at FootballPerspective.com, but instead, I’ll share some random thoughts on each franchise based on well, whatever springs to mind. We’ll kick things off with look at the San Francisco 49ers.]

The 49ers are an interesting team to me because they seem like the ideal candidate to regress. Generally, teams that make huge jumps in one season are better candidates to fall back to the pack than elite teams with a history of success. Additionally, defensive teams are generally less likely to retain their success than offensive teams. But since I don’t expect you to just believe me…

I looked at all teams since the AFL-NFL merger in 1970 that won at least 75% of their games (San Francisco went 13-3 last year) and then separated them based on their records in the prior season (the 2010 49ers went 6-10). There were 155 of them, and how they performed in the year before (Year N-1) their elite season was relevant in determining their record in the year (Year N+1) after that big season. The table below breaks down the teams based on their winning percentages in Year N-1 (for our purposes, that’s 2010 for the 49ers) and then shows how well they performed in Year N+1 (for our purposes, the 2012 49ers):

Just so we’re all on the same page, the top row of that table informs us that of the 155 teams to win at least 75% of their games, 24 of them won over 80% of their games in Year N-1. On average, those teams won 86.3% of their games in Year N-1, 79.7% of their games in Year N, and then 67.2% in Year N+1. The 49ers would represent a team in the bottom row. There have been 25 teams like the 2011 49ers who won at least 75% of their games after having a losing record the prior year (on average, those teams won just 37% of their games – just like the 2010 49ers); in the following year (e.g., the 2012 49ers) those teams won just 53.6% of their games.

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[Five years ago, my friend and Pro-Football-Reference.com founder Doug Drinen wrote the predecessor to todaay’s article, but refused to go with this title. The principles remain fundamental to advanced analysis of any sport, so today I’ll be revisiting them with current examples.]

Our brains are really good at making connections and finding patterns. In The Believing Brain, Michael Shermer argued that we’ve made it to where we are today precisely because of our ability to do just that:

A human ancestor hears a rustle in the grass. Is it the wind or a lion? If he assumes it’s the wind and the rustling turns out to be a lion, then he’s not an ancestor anymore. Since early man had only a split second to make such decisions, Mr. Shermer says, we are descendants of ancestors whose “default position is to assume that all patterns are real; that is, assume that all rustles in the grass are dangerous predators and not the wind.”

Of course, not all patterns are real, and sometimes that rustle is just the sound of the wind. Just because you see a surprising split — maybe a player dominated the second half of the season after a slow start — doesn’t mean that the “trend” is real. For example, here are some splits from the 2011 season:

Reggie Wayne was much better against teams that wear the color blue than when facing teams that have no blue in their uniforms. Here is his weekly production (the last column represents his fantasy points) when playing against teams that do not have blue as a color in their uniform:

Week	Opp	Rec	Yd	TD	FP
17	jax	8	73	0	15.3
5	kan	4	77	0	11.7
6	cin	5	58	0	10.8
2	cle	4	66	0	10.6
4	tam	4	59	0	9.9
14	rav	4	41	0	8.1
9	atl	4	30	0	7.0
7	nor	3	36	0	6.6
3	pit	3	24	0	5.4
10	jax	3	13	0	4.3
Avg		4.2	47.7	0	9.0

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Gene Stallings coached in the NFL in the late ’80s, in between the Jim Hanifan and Joe Bugel eras of Cardinals football. He was the man who led the team as the franchise relocated from St. Louis to Phoenix. He coached under Tom Landry for over a decade in Dallas. But Gene Stallings will always be remembered for working under Bear Bryant and for embodying what it meant to coach Alabama football.

Stallings played on Bryant’s famous Junction Boys team at Texas A&M, and coached under Bryant when the Crimson Tide won national championships in ’61 and ’64. After his failed stint in the NFL, Stallings returned to Alabama, this time as the head coach. His crowning achievement was winning the 1992 national championship, capping a 13-0 season.

So why the background on Stallings today? One of the fun things about owning a website is seeing where your traffic comes from. I noticed a bunch of hits were coming from RollBamaRoll.com. So I went to the site to see what was driving the traffic (as it turns out, a random link to this passer rating article) and I found this great quote by Stallings on another page:

Everyone keeps talking about our game with Miami [in the 1993 Sugar Bowl]. The reason we won against Miami is this: We had the ball 15 minutes more than they did. We ran the ball for 275 yards against Miami. They ran the ball for less than 50 yards. When the game was over, we won. After a game, it may not look good. The alumni may be asking why we are not entertaining them. Let me assure you that our job is to win football games. You win football games by running the ball, stopping the run and being on the plus side of giveaway-takeaways.

I think every coach ^[1]Mike Martz excluded, of course. at every level has, at some point, uttered a phrase to essentially the same effect. It is quintessential Alabama football, but it could have just as easily come out of the mouth of Greasy Neale or Bill Cowher or Vince Lombardi. Of course, whenever I read a quote like that, two immediate questions come to mind. Is it true? And how can I determine if it’s true?
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On Tuesday, I looked at running back records and argued that Steven Jackson had taken the mantle from Ollie Matson as the most prominent elite running back to have toiled for losing teams for the majority of his career. It’s easy to feel bad for a player like Jackson, relegated to consistent attack as the focal point of opposing defenses for a decade, continuously grinding out yardage while playing for bad teams.

Things are a little different for wide receivers. In fact, it’s often easier for wide receivers to produce better stats while playing for bad teams, since trailing teams are forced to throw later in games. Further, wide receivers don’t face the constant pounding that running backs encounter, making them slightly less sympathetic figures. Still, it’s an interesting question, and one that’s easy enough to answer. Which wide receivers have played for the best and worst teams? Any guesses? The results, after the jump.

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Which stats should be used to analyze quarterback play? That question has mystified the NFL for at least the last 80 years. In the 1930s, the NFL first used total yards gained and later completion percentage to determine the league’s top passer. Various systems emerged over the next three decades, but none of them were capable of separating the best quarterbacks from the merely very good. Finally, a special committee, headed by Don Smith of the Pro Football Hall of Fame, came up with the most complicated formula yet to grade the passers. Adopted in 1973, the NFL has used passer rating ever since to crown its ‘passing’ champion.

Nearly all football fans have issues with passer rating. Some argue that it’s hopelessly confusing; others simply think it just doesn’t work. But there are some who believe in the power of passer rating, like Cold Hard Football Facts founder Kerry Byrne. A recent post on a Cowboys fan site talked about Dallas’ need to improve their passer rating differential. Passer rating will always have supporters for one reason: it has been, is, and always will be correlated with winning. It is easy to test how closely correlated two variables are; in this case, passer rating (or any other statistic) and wins. The correlation coefficient is a measure of the linear relationship between two variables on a scale from -1 to 1. Essentially, if two variables move in the same direction, their correlation coefficient them will be close to 1. If two variables move with each other but in opposite directions (say, the temperature outside and the amount of your heating bill), the CC will be closer to -1. If the two variables have no relationship at all, the CC will be close to zero.

The table below measures the correlation coefficient of certain statistics with wins. The data consists of all quarterbacks who started at least 14 games in a season from 1990 to 2011:

As you can see, passer rating is indeed correlated with wins; a correlation coefficient of 0.51 indicates a moderately strong relationship; the two variables (passer rating and wins) are clearly correlated to some degree. Interception rate is also correlated with wins; there is a ‘-‘ sign next to the correlation coefficient because of the negative relationship, but that says nothing about the strength of the relationship. As we would suspect, as interception rate increases, wins decrease. On the other hand, passing yards bears almost no relationships with wins — this is exactly what Alex Smith was talking about last month:
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