It’s become trendy in this space and many others for stats folks to rail against bad 4th down decisions. It’s even trendier to do it when those conservative decisions backfire, leading to losses. But analyzing any decision — and especially decisions about whether to go for it or kick on 4th down — should not be done with the benefit of hindsight. So today, I’m going to rail against John Harbaugh, Bill Belichick, and Mike McCoy, who made some awfully timid 4th down decisions but won on Sunday. And while one could argue that they won because of those decisions, the better argument, I believe, is that they won in spite of them.

Trailing by 4 with 5:03 remaining, the Ravens kick a Field Goal on the 3-yard line

Harbaugh is no stranger to meek 4th down decision making; in fact, he’s no stranger to this particular brand of conservative coaching. Last year, he sent out the kicker when, trailing by 6 points with just over four minutes remaining in the game, the Ravens faced a 4th and 5 from the 6 yard line. Both Jason Lisk and I wrote about the silliness of this decision, which resulted in a Buffalo 23-20 victory.

Facing similar circumstances — a 4-point lead and an extra minute remaining makes it less objectionable to kick the field goal, but being on the 3-yard line makes it even worse — Harbaugh again sent out Justin Tucker to take the points.  That decision cost the Ravens 0.22 expected wins; according to Advanced Football Analytics, the decision to kick a field goal instead of going for it dropped Baltimore’s win probability from 54% to 32%.

As Mike Tanier facetiously wrote, this just set up the ultimate Ravens end game: one bomb from Joe Flacco and one kick by Tucker is all the team would need to win.  Sure enough, Flacco hit Steve Smith for a 32-yard catch, and Tucker kicked the chip shot for the win.  The Ravens wound up having two additional possessions: after Tucker made it a 1-point game, the Browns and Ravens traded 3-and-outs, and the Browns went 3-and-out again before giving Baltimore one final possession with 1:58 remaining.

At the time of the decision to send Tucker out for a field goal, Brian Hoyer was 19 of 22 for 290 yards and a touchdown. He wound up throwing incomplete on his last three passes of the day. But if not for two Cleveland three-and-outs — the only two of the day — Harbaugh’s decision to cost his team 22 points of win probability would be generating much more backlash today. [continue reading…]

I was invited back for a third visit over at the Advanced Football Analytics (formerly Advanced NFL Stats) podcast. You can click here to listen to me and Dave Collins discuss the Jets, Game Scripts, some week three predictions, and more. Give it a listen; the AFA podcast is great, and I’d recommend listening to it every week (you can click the following links to subscribe for free to the AFA Podcast on iTunes or Stitcher.)

Today I want to look at how traditional rushing statistics compare to rushing Expected Points Added, one of the main stats used over at Advanced Football Analytics. In my analysis, I used the EPA numbers for each team in each season from 2002 to 2013.

Stickiness from year to year

Yards per carry is not a sticky metric: by that, I mean, it is not very consistent from year to year. The correlation coefficient between a team’s yards per carry in Year N and yards per carry in Year N+1 was just 0.31. Sometimes the square of the correlation coefficient is described in terms of “explanatory power”: loosely speaking, this means roughly 10% of a team’s YPC average in Year N+1 can be explained by its YPC average in Year N.

Now, a lot of metrics aren’t sticky from year to year, because the NFL is a highly competitive league. In fact, Rushing EPA per play has a lower correlation coefficient from year to year at just 0.30. That’s a strike against EPA. On the other hand, Burke’s success rate metric has a CC of 0.39, which is more impressive. The CC for Net Passing Yards per Attempt year over year is 0.43. [continue reading…]

A couple of weeks ago, Brian Burke of Advanced Football Analytics (formerly Advanced NFL Stats) wrote a great post on the value of a first down. From that post, we concluded that the marginal value of a first down is 9 yards, and we’ve previously determined that the marginal value of a touchdown is 20 yards. Therefore, we can create an Adjusted Yards per Carry statistic, which can be calculated as follows:

Adjusted Yards per Carry = (Rushing Yards + 20 * Rushing TDs + 9 * Rushing First Downs) / Rushes

If we use this metric to analyze the 2013 season, how would it look? Last year, the Eagles averaged 5.13 yards per carry and 8.29 Adjusted YPC, courtesy of the fact that the team led the NFL in rushing first downs. Philadelphia also ranked 1st in the NFL in both of those metrics and in overall rushing yards. [continue reading…]

What is the value of a first down? By that I mean, how many marginal yards is a first down actually worth? Here’s another way to word the question: If 3 first downs and 80 yards are worth X, then 2 first downs and [???] many yards are equal to X?

Calculating the marginal value of a yard isn’t easy. In fact, it’s been bugging me for years, because I’ve never quite been sure how to derive them. Then, a light bulb went off in my head: I needed to reach out to Brian Burke. I had an idea, but not the data or the means to execute.

Burke, of course, runs the fantastic website Advanced Football Analytics (formerly Advanced NFL Stats). I asked him if he would run some queries, and Brian was kind enough to do so. Fortunately, Brian’s not just a guy with access to lots of data, but one of the smartest minds in the industry. I wholeheartedly endorse his methods below, and I’m very thankful for his help. On top of running the numbers, he also provided an excellent writeup on his work. What follows are Brian’s words and analysis.

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To estimate the value of achieving a 1st down without counting any of the value of the yardage gained, we can use the Expected Points model. The value of the 1st down itself minus yardage value will be the discontinuity in EPA when a play’s gain crosses the threshold for a 1st down. That discontinuity represents the value of the conversion apart from any yardage gained.

For example, on 2nd and 10, the EPA would increase smoothly for each yard gained up to 9 yards gained, then jump to a much higher EPA crossing the 10-yard mark where the conversion occurs. After that point, the EPA should increase smoothly again with each marginal yard gained above what was needed for the conversion.

Here is an illustration. The Y-axis represents Expected Points Added, the X-axis the amount of yards gained on the play.

The EPA for a 9-yd gain is 0.57, and the EPA for a 10-yd gain is 1.04. That’s a discontinuity of 0.47 EP, meaning that the 1st down itself is nearly equivalent to the 9-yards gained up to the point of conversion.

But we also need to correct for the yardage value of that 10th yard. One yard of field position is generally worth 0.064 EP. So in this case the discontinuity itself is worth 0.47 – 0.064 = 0.41 EP.

If we wanted to assign a “bonus” of yards to a player who is credited with achieving the conversion over and above the yardage itself, we could use this value’s yardage equivalent. 0.41 EP / 0.064 EP/yd = 6.4 yds. That’s the bonus for 2nd down and 10, but there are many other down and distance situations to consider.

For example, on 3rd and 10, the discontinuity is 1.57 EP, equivalent to nearly 25 yds. First and 10 is very strange because the discontinuity is negative. This makes sense, however, because an offense should prefer a 2nd & 1 to a 1st & 10 anywhere on the field. It would be silly to penalize a player for gaining the extra yard to convert, so my opinion would be to say the EP bonus for a conversion on 1st down is zero.

After examining a smattering of 2nd and 3rd down situations, the 2nd-down bonus EP is about 0.35 and 3rd-down bonus EP is roughly 1.4.

4th down conversions would obviously mean a very large bonus EP. They essentially have the value of a turnover–close to 4 EP or so. Since 4th downs are qualitatively different (and relatively rare) I’m going to set them aside.

In general, 32% of conversions come on 1st down, 38% come on 2nd down, and 30% come on 3rd down. So the weighted value of a conversion alone would roughly be:

[0.32 * 0] + [0.38 * 0.35] + [0.30 * 1.4] = 0.55 EP

The conversion bonus of 0.55 EP can be translated into yards by dividing by 0.064 EP/yd, which ultimately makes the equivalent yardage bonus for a conversion: 8.7 yards.

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Figuring out the value of a first down will have many applications for Football Perspective going forward. Please leave your thoughts in the comments, as I’d love to hear what you guys have to say. And thanks again to Brian for his great work.

In early October, I went on the Advanced NFL Podcast with host Dave Collins.  This time of year is fruitful for good discussion, so Dave invited me back on the show. In Dave’s words, we began

by breaking down the historical context of Peyton Manning’s single season passing touchdown record. They then cover the Carolina Panthers and break down the changes they’ve made over the past year, the storylines surrounding Cam Newton, and how overall team performance can sometimes obfuscate an individual player’s development

Next, Chase takes to his soapbox to make the case that the Jets should fire Rex Ryan and explains how retaining him would set a unique historical precedent. Next, they turn their sights to the Giants and discuss what to make of Eli Manning’s interception spike.

The episode concludes with a look ahead to the week 17 Bears/Packers and Cowboys/Eagles matchups. Chase weighs in on what he’s most excited for in this year’s playoffs, and why playing a Superbowl outdoors might actually be more fair than playing in a dome.

You can listen to it here, and can subscribe to the podcast on iTunes here.

Advanced NFL Stats has rolled out a podcast this year, and host Dave Collins invited me on the show this week. You can hear me ramble for 35 minutes here, where we discuss two point conversions, game scripts, and gush about Peyton Manning. Brian Burke has had a great site for years, but Dave is now bringing yet another way to learn about Advanced NFL Stats — you can subscribe to the podcast on iTunes here.

You know the name Pete Gogolak, don’t you? The former Buffalo Bill placekicker is a famous figure in football history for two reasons. First, he played a key role in the merger between the AFL and NFL in the 1960s. ^[1]Gogolak was the first AFL player stolen by an NFL team. In 1965, Bob Timberlake succeeded on just one of his fifteen field goal attempts for the Giants. That prompted a desperate Wellington Mara to … Continue reading He’s also remembered for what he did on the field: Gogolak is widely credited with being the first soccer-style kicker in pro football history.

But Gogolak’s impact wasn’t limited to identifying the optimal technique for kicking a football: he also helped usher in an era of specialists. In the early days of the NFL, there was no room for a specialist as rosters were tiny and players played on offense, defense and special teams. Unlimited free substitution wasn’t permanently instituted until 1950, and as recently as 1963, teams were limited to just 37-man rosters.

Once teams were allowed to roster more players, and a certain unique brand of kicking was proven to be superior, a more specialized NFL emerged. In 1949, nobody would have signed a soccer-style kicker, or any person who could only kick a football. We joke now that kickers aren’t real football players, because back in 1949, a kicker would also need to play tight end or free safety. The idea that 5’11, 182-pound, 42-year-old Jason Hanson could be a contributing member of an NFL team is as noncontroversial in 2012 as it would have been laughable in 1952. It’s not going to take 60 years before an advanced statistical analyst — perhaps the front office version of a kicker — becomes a contributing member of an NFL organization.

This weekend, I sat down with Brian Burke, the founder of Advanced NFL Stats, a fantastic website on football, statistics and game theory. Burke’s win probability calculator has been one of the most exciting innovations in our industry. In Part II of this series, I’ll be interviewing Football Outsiders’ Aaron Schatz. Neither person is a threat to Ron Rivera’s job security anymore than Jason Hanson is a threat to steal Calvin Johnson’s job. Specialization is the way of the world, and hiring someone trained in the art of decision-making isn’t any different than choosing to hire a lawyer or doctor. We can’t expert anyone to be an expert in everything.
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