Play-by-Play Data Update

The NFL play-by-play data set has been updated through week 12 of the 2013 season. It's available here, or via the main drop-down menu under the About tab. Nearly every NFL play since 2002 is included for your research purposes. Happy crunching.

The 2013 Eagles and the Criteria of a Super Bowl Contender

It's no secret that scoring has risen in the NFL.  2013 is on pace to be the highest-scoring season in league history, as teams are averaging 23.3 points per game.  After sticking around the 18-20 point range from 1990 to the early 2000s, point increases have experienced an accelerated growth as a consequence of the league's emphasis to liberate offenses.

And yet, there remains a perception that flashy high-scoring teams are only capable of regular-season success, possessing some ambiguous inherent flaw that makes them go kaput in January.  Recent examples include the 2010 Falcons, 2010 Patriots, 2011 Packers and 2012 Broncos.  All these squads represent high-flying number one seeds whose pass-happy offenses flamed out in stunning fashion during a Divisional Round upset.

Playoff Projections - Week 12


All of the numbers below come from Chris Cox at NFL-forecast.com. His app uses the win probabilities from the ANS team efficiency model to run a Monte Carlo simulation of the remaining NFL games thousands of times. Based on current records, our estimates of team strength, and knowledge of the NFL's tie breaking procedures we can come up with some pretty interesting predictions of how each team will fare come the end of the season. If you want to use a different model or just fiddle with the numbers by hand, go ahead and download the app yourself.

Week 12's biggest movers

Capitalizing on Washington's anemic passing performance, San Francisco ended its losing streak. Because Seattle has the West essentially wrapped up, the Cardinals and the loser of the South divisional race are San Francisco's primary rivals at this point. Until recently they also had to worry about the second place team in the north, but the top 3 teams in the division all going winless last week effectively ended that concern. Based on all this, the 49ers jumped 23% to a 67% playoff probability.

Win Probability Calculator Upgrade - New OT Rules

After the MIN-GB overtime game Sunday, you may have stopped by the Win Probability Calculator tool to see what GB should have done on 4th down on the goal line on their first possession. As luck would have it, I rolled out a big upgrade to the calculator just the night before that incorporates the three various game states in overtime.

Under the 'Period' input, there are the 4 quarters, plus 3 overtime states, corresponding to:

-'First possession', in which a team can score a TD to win or a FG to begin...
-'Down by three', in which a team has all 4 downs to move down the field to win with a TD or match the FG to begin...
-'Sudden death', which begins upon any change of possession with a tie score.

The previous version of the calculator still relied on the old pure-sudden-death overtime format. With so few examples to test against, I'm sure there are a few bugs or discontinuities waiting to surprise us, so please note any discrepancies in the comments here. But remember that not all unexpected results are errors--The new format does have its quirks.

The new overtime model has already been working for the WP graphs and team/player stats. Soon I'll roll it out for the 4th Down Calculator too. And more big upgrades to the WP calculator tool are on their way.

Game Probabilities - Week 13

Game probabilities for week 13 are available at the New York Times. This week I look at Aaron Rodgers's value to the Packers.

...The model used here to produce the game probabilities is a “parametric” model, meaning its inputs are parameters that can be varied easily. That’s obviously a good thing, as team statistics certainly vary from week to week. It’s also handy because those parameters can be manually adjusted to account for injuries and just to play what-if...

By replacing Rodgers’s numbers with Flynn’s, and holding all other factors as is, we can get a rough idea of how the game probability should change. Unsurprisingly, the numbers would now heavily favor Detroit...

Team Efficiency Rankings: Week 12

The old adage that a championship team must "run the ball and stop the run" is out of date, as this site has expounded in great detail.  If it's true that today's NFL is a passing league (spoiler: it is), then the exact opposite of the original saying must be true, right?  It seems logical to assume that in order to win the Super Bowl, a team must be able to pass and stop the pass.

While the first part of that formula is likely true, the second part is a bit more ambiguous.  Super Bowl XLVI pitted two below-average pass defenses in the Giants and Patriots, but the year before, the Packers and Steelers met for the title with two of the three best pass defenses in the league.

Those are only two examples, but there's nothing that tells us that a super pass defense is absolutely essential to a Super Bowl champion or contender.  Of course, there's no denying that it helps—last year, only the Patriots, Redskins and Colts made the postseason with a negative pass D EPA.

Therefore, if we consider good pass defense an important but not indispensable quality, that bodes well for a contender who, despite this past weekend's results, is showing quiet improvement in that area.

Was Belichick Right to Take the Wind in OT?

I was surprised when Bill Belichick chose to take the second possession (and risk no possessions) in OT against Peyton Manning and a team that had scored 31 points in four quarters. Although the new OT format mitigates the advantage of the team with first possession, it's still there to the tune of about 56% to 44%.

The advantage of wind must have felt fairly strong to Belichick. His team captains thought he was crazy. At the time, it was impossible to tell from the comfort of my sofa how bad the wind was, but I was curious if we could see the effect statistically.

Podcast Episode 10 - David Romer

David Romer, professor of economics at UC Berkeley, is on the podcast this week to discuss why coaches should be more aggressive on fourth down. David is the author of "Do Firms Maximize? Evidence From Professional Football" and in this interview, he explains his novel approach to analyzing fourth down decision-making. He outlines reasons why coaches are incentivized to make sub-optimal choices and how they can improve their team’s chances of winning by following his advice.

Professor Romer explains why "critical probabilities" are important, and why the "dead zone" on the field presents unique choices for an offense stalled on fourth down. He also tells the story of how after hearing Bill Belichick's critique that his paper didn’t account for the existence of momentum, he amended the writing to include an examination of why momentum in the NFL does not have a measurable effect on game results. For more on the professor's paper, check out the following links:

- Brian Burke’s review. In his response, Brian explains why the professor’s research may actually underestimate the effects of his proposed offensive strategy. [Edit: Prof. Romer set me straight a few yrs back. I overlooked that the paper makes the same point I made. -Brian]

- New York Times coverage

- ESPN the Magazine essay by Michael Lewis

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The New Overtime Format Is a Complicated Mess--Here's How to Fix It

Dear Competition Committee:

The ostensible purpose of NFL overtime is, first and foremost, to declare a winner and avoid a tie, and second, to do so quickly. If ties were acceptable, I assume the league would not bother to even have overtime.

In recent years, as offenses gradually gained an ever stronger upper hand over defenses, it became clear that the former sudden death format gave too much advantage to the winner of a trivial coin flip. We saw time and time again as a team won the coin toss, got a decent return, earned a couple first downs, and kicked a long field goal without even a whimper from the unlucky loser of the coin flipping contest. Something needed to be done.

And, unfortunately, "something" was done. The current format is a mess because its effects are contrary to both stated purposes of overtime. It increases the chances of a tie while a prolonging the overtime period.

The new rules are complex and non-traditional. In the event the team with first possession scores a field goal, the opponent now has a drive opportunity with all four downs and no pressure of time to respond. And the rules still favor the team that wins the coin toss.

Here is what I think is a much better and far more elegant solution, which is fair, traditional, avoids ties, and leads to much quicker resolutions:

Sunday's Numbers Have Been Crunched

Sunday's numbers are now available, including advanced stat box scores, top players of the week, team stats, and season leader boards.

Advanced stat box scores
Top QBs of the week
Top RBs of the week
Top WRs of the week
Top TEs of the week
Top Defenders of the week
Advanced team stats
Offensive player season leaders
Defender season leaders
Team Viz
Position Leaders Viz
QB Viz
RB Viz

Fumble Rate by Temperature

The title says it all. With Sunday's night's fumble fest in the books, I thought I'd take a quick and dirty look at how cold temperature affects fumbling. It was 19 degrees in Foxboro when I checked the weather there in the 4th quarter.

I looked at all plays from 2000 through the 2012 regular season, excluding kneel downs and spikes. I counted all fumbles, not just fumbles lost. Keep in mind the sample sizes greatly diminish at the temperature extremes.

Here is the breakdown:

McCarthy Makes New OT Mistake

Kicking a field goal on the two is like kissing your sister.

I could not have said it better myself. Nothing is more annoying when trying quantify a season and run simulations than coding for a tie. The Packers and Vikings tied 26-26 on Sunday after both teams kicked field goals in overtime. On the opening drive, Matt Flynn led the Packers to the Vikings 2-yard line before Mike McCarthy decided to kick a field goal, sending the game into the "chance to match down three" format. In the new overtime format, was this the optimal decision?

Brady vs. Manning: Who Really Has the Upper Hand?

There are lots of different ways to measure who truly has "the upper hand" in the Tom Brady-Peyton Manning rivalry.  Brady supporters will cite his teams' 9-4 head-to-head record as the decisive edge, while the Manning camp may point out that their quarterback has the better stats over the 13 meetings.  These arguments dovetail with each quarterback's general reputation—Brady as the winner, Manning as the stat-sheet stuffer.

Of course, neither Brady nor Manning play defense, so a "head-to-head" comparison is a bit short-sighted to begin with.  Jake Plummer was 2-0 against Brady, and Jay Fiedler put up better numbers in his four head-to-head matchups against Manning.  Somehow, I doubt a "Fiedler vs. Manning" post would generate much debate.

So how do we begin to truly evaluate which quarterback has performed better in 13 Manning vs. Brady games?  Well, let's start by looking at their WPA, EPA and passing success rate (SR) during each of their games:

Playoff Projections - Week 11


All of the numbers below come from Chris Cox at NFL-forecast.com. His app uses the win probabilities from the ANS team efficiency model to run a Monte Carlo simulation of the remaining NFL games thousands of times. Based on current records, our estimates of team strength, and knowledge of the NFL's tie breaking procedures we can come up with some pretty interesting predictions of how each team will fare come the end of the season. If you want to use a different model or just fiddle with the numbers by hand, go ahead and download the app yourself.

San Francisco and Green Bay fall

After week 8, we gave the 49ers a 94% chance of making the playoffs. Two losses have contributed to their current odds of 44%, but they are also being squeezed out of wild card contention by the success of their peers. The simultaneous win streaks by the Panthers and Cardinals led to jumps in playoff probability of 41% and 26%, respectively, in that 3 week span. At this point, their best hope is sneaking in to that 6th NFC slot.

Green Bay's third straight loss has put them in a similar situation. What was an 83% chance 3 weeks ago is now just 33%. They have a relatively easy game against the Vikings this week before the crucial Thanksgiving match up versus the Lions.

Game Probabilities - Week 12

Game probabilities for week 12 are available at the New York Times. This week I look at the Jets' strange Pythagorean record.

...This season the Jets are doing their best to defy James, Pythagoras and their formulas. They have scored 183 points and allowed 268 on their way to a 5-5 record. That’s a net point difference of -85, which is second worst in the league, topping only the Jaguars. According to the Pythagorean expectation, the Jets should have about a .265 winning percentage, good for a 3-7 record or perhaps 2-8...

Podcast Episode 9 - Brian Burke

Brian Burke is back to discuss momentum, clock management and topics from his weekly roundups. In his recent post on momentum, Brian used three different methods to investigate whether momentum is a measurable phenomenon in NFL games. Dave and Brian discuss why momentum is such a popular concept and hypothesize why coaches and analysts seem to rely so heavily on the idea. They also discuss Brian’s article on clock management, and why it’s unlikely that truly non-zero sum scenarios exist in a football game. They finish up the show with a "rapid fire roundup" of some interesting articles and analysis from around the web.

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Momentum Part 2: The Effect of Momentum-Swinging Events on Game Outcomes

Recently I tried to detect the existence of momentum within an NFL game. I examined drive success based on how 'momentous' the manner in which the offense gained possession. Admittedly, that analysis only measures one aspect of momentum. In this post, I'll take the analysis a step further and look at how a team's chances of winning are affected following several momentum-swinging types of events. This approach examines the potential effect of momentum on the entire remaining part of a game, not just on the subsequent drive.

Like the previous analysis, I relied on how possession was obtained as an indication of a momentum-swing. For all drives from 1999-2013 ( through week 8), I compared a team's expected chances of winning (based on time, score, field position, down and distance) with how often that team actually won. I divided the data among three categories: possession obtained following a momentous play, possession obtained following a turnover on downs, and possession obtained following a non-momentous play.

Momentous obtainment includes fumble recoveries, interceptions, muffed punts, blocked kicks, and blocked field goals. I excluded missed field goals from the analysis because it was unclear to me how momentous they are. They are often thought of as big momentum changing events in close games but are too common (almost 20% of all kicks) to truly be momentous.

Team Efficiency Rankings: Week 11 [Corrected]

[Edit: My personal apologies for a bug since 2 weeks ago that penalized teams who had already had their byes. (I believe) it's been fixed, and I've made the corrections to the rankings below. -B.B.]

Strength of schedule is a fickle variable, one that should tell us more about a particular opponent but really does not.  Though this formula does account for S.O.S, that's not always the best indicator of whether or not a team has faced "legitimate" competition.

Despite what Bill Parcells may have you believe, a team is not always what their record says they are.  They are often a flawed representation of late-game variance and fluky injuries, especially when you're splitting hairs among closely contested teams.  That's how you end up with Tampa Bay being the 20th-ranked team in Football Outsiders' DVOA despite entering the week a single win.

Still, there are instances where a team shows some pretty alarming splits among the haves and have-nots.  In the case of one likely playoff team, that makes for some troubling signs going forward.

Newton's Football

Forbes writer Allen St.John and materials scientist Ainissa Ramirez recently wrote a book titled Newton's Football on various intersections between science and our favorite sport. It's right up ANS' alley. Allen has an article at Forbes with an excerpt from the book:

"The theory that coaches were purely motivated by job security and didn’t want to go against the conventional wisdom, that didn’t quite satisfy me," says Brian Burke of Advanced NFL Stats. Week in and week out, Burke analyzed games and saw evidence that NFL coaches were costing their teams yardage, 1st downs, and, ultimately, games because of the questionable decisions they were making. He further noticed that those coaches almost invariably erred on the side of caution. But why?...
"In terms of team building, risk taking is good," Burke argues. He notes that in any given year the average NFL team enters a season with a Bayesian prior expectation of winning a Super Bowl that’s 1 in 32. "You’re a 31–1 underdog. You want to take chances," Burke explains. "It’s okay to miss the playoffs and win five games instead of seven. It doesn’t hurt you that much. But teams are very conservative. They'd rather win a few more games and avoid having a terrible record."

Is the Revolution Over? Did We Win?

"The Revolution Was Televised. The fourth down revolution is over. Going for it won."

Is Mike right? Did going for it really win? Mike makes a the case, and cites several promising examples of unconventional 4th down decisions from one Sunday afternoon earlier this season:

"-The Lions going for it on 4th-and-goal from the two-yard line, early in their win over the Cowboys.
-The Dolphins going for it on 4th-and-1 from the Patriots' 38-yard line, in the second quarter.
-The Patriots going for it on 4th-and-4 from the Dolphins' 34-yard line, while leading by three points in the fourth quarter.
-The Bengals going for it on 4th-and-inches from the 1-yard line, while leading 14-0 against the Jets.
-The Broncos scoring a 4th-and-goal touchdown to tie the game at 21 against the Redskins, in the third quarter.
-The Packers converting a 4th-and-3 from their own 42-yard line, setting up a touchdown to increase their lead to 31-17."

I think Mike is right to point out some very interesting cases where coaches are making some notable decisions, but the revolution is far from complete. I would suggest that an avalanche is the better analogy than revolution. One day there may be an avalanche of aggressive 4th down decisions, but right now we're only seeing a few rocks trickle down the mountainside. It's not that there haven't been bold examples of enlightenment. It's just that there are so many opportunities that coaches have spurned.

Momentum 1: Scoring Rates following 'Momentum-Swinging' Events

Momentum might be one of the most over-cited concepts in sports. It's an idea borrowed from physics, and is something we witness every day. We see it in rising tides, building storms, and boulders rolling downhill. But does such a concept apply to sports? Certainly, better teams will likely continue to prevail, and lesser teams will likely continue to lose. But that's not momentum. It's just better teams being better.

In this article, I'll explain why I think we see momentum when it's not really there. And to test the existence of momentum within NFL games, I'll compare the results of drives following 'momentum-swinging' events with those following non-momentum-swinging events.

For momentum to be a real thing in sports, it needs to have some connection to reality beyond the metaphysical and metaphorical. The theory is that good outcomes are emotionally uplifting, which in turn leads to better performance, which then feeds upon itself. It's understandable to believe in game momentum when we see games like this each week:

Sunday's Numbers Have Been Crunched

Sunday's numbers are now available, including advanced stat box scores, top players of the week, team stats, and season leader boards.

Advanced stat box scores
Top QBs of the week
Top RBs of the week
Top WRs of the week
Top TEs of the week
Top Defenders of the week
Advanced team stats
Offensive player season leaders
Defender season leaders
Team Viz
Position Leaders Viz
QB Viz
RB Viz

Lions' Odd Fake Field Goal

After stopping a Detroit Lions' fake field goal attempt, down 23-27, the Pittsburgh Steelers went on to score two unanswered touchdowns - clearly a product of momentum - and win the game 37-27. When the Lions faked the field goal, I was a little bit baffled. Normally, inside the 10 or so it makes sense to go for it because even with a failure, opposing offenses are pinned so deep in their own territory - depending on distance-to-go. 4th-and-5, with vertical space restricted at the 10-yard line, is not an easy conversion; it converts league-wide around 36%. Based purely on efficiency (not including time remaining or score differential), a field goal results in greater return (+0.16 EP over going for it). It's not a huge difference, as the break even point is only 39% conversion probability.

Roundup 11/16/2013

People will overpay to control their own payoffs. "The average participant is willing to sacrifice 8% to 15% of expected asset-earnings to retain control." This is consistent with the notion that teams that trade away too much to move up in the draft.

Using tracking cameras to analyze drives to the hoop in the NBA.

Keith takes Nantz and Simms to task for their misunderstanding of when to go for 2. This situation is not uncommon--I mean that teams should go for 2 earlier rather than later because of the value of information, not that announcers don't understand what they're talking about. (Although that happens plenty.) Here's an example from just a couple weeks ago:

Playoff Projections - Week 10


All of the numbers below come from Chris Cox at NFL-forecast.com. His app uses the win probabilities from the ANS team efficiency model to run a Monte Carlo simulation of the remaining NFL games thousands of times. Based on current records, our estimates of team strength, and knowledge of the NFL's tie breaking procedures we can come up with some pretty interesting predictions of how each team will fare come the end of the season. If you want to use a different model or just fiddle with the numbers by hand, go ahead and download the app yourself.

Week 10's big movers

Because New Orleans won, Carolina's chances of winning the division stayed pretty static, but the chances of a Panthers wild card berth sky rocketed. The 32% bump came almost entirely at the expense of the team they beat, San Francisco. Both teams are now 6-3 but Carolina holds the head-to-head tie breaker, which is especially significant because neither team is likely to win its division. San Francisco now only has a 4% chance of beating out the Seahawks in the West.

Game Probabilities - Week 11

Game probabilities for week 11 are available at the New York Times. This week I do a back of the envelope analysis of how likely it would be for a team like the Chiefs to finish the regular season undefeated..

...But we know N.F.L. games are not coin flips, so how good would a team have to be to have a 50/50 shot at going undefeated through 16 games? If a team were so good that it had a 90 percent chance of winning any one game, it would only have a 19 percent chance of going 16-0. In fact, a team would need a 96 percent chance of winning any one game before it had better than even odds of going undefeated. So it’s a rare thing for a reason...

Team Efficiency Rankings: Week 10

This late into the season, there aren't really any more flukes.  Injuries are really the one major variable that can still change a team's fortunes, but it's impossible to know when landscape-changing losses like Aaron Rodgers will happen.

So if we (mostly) accept the data that 10 weeks have shown us, the teams in the top and bottom 10 are likely to stay that way.  Looking at the rankings from this time last year, eight of the top-10 teams remained there at the end of the season, and eight of the bottom-10 stayed near the basement.

The middle is still terribly ambiguous, and it's probably best to wait for a few more returns before making any more definitive evaluations.  The last couple weeks have seen me make some pretty foolish-looking predictions about these teams (more on that soon), so we'll step aside from the middle class for a week.

Instead, let's take a look at arguably the biggest surprises from the top and bottom third, and try to explain how they got there.

End of Half Clock Management

I'm watching a game right now where there's over a minute left in the 2nd quarter. The ball is at midfield and it's 4th and long. Both teams have all three timeouts, but neither team used any. The punting team is standing around letting the seconds tick away, while the receiving team is patiently waiting for the snap.

I think this is irrational. Football is a zero-sum game. Whatever is good for me is equally bad for you, and vice versa. So if stopping the clock right now is not what you want, then it must be what I want. It can't be possible for both teams to benefit from allowing the clock to run down. One or the other team derives an advantage, however small, from stopping the clock.

The only plausible exception I can think of is when the possibility of either team scoring is so remote that the cost of potential for injury on the remaining plays exceeds the value of whatever advantage could be squeezed from trying to pursue a score. In this sense, the game becomes non-zero-sum.

But I think it's more likely that one or both of the teams are excessively pessimistic. The punting team is worried that the receiving team might have enough time to put together a scoring drive, and the receiving team is worried they might turn the ball over or be forced to punt again from deep in its own territory.

Do Comeback Wins Equal Future Regression?

Last week, Brian wrote a post examining teams that have blown multiple games within a season in which their win probability was 95 percent or higher.  The "blown game factor" statistic he referenced is essentially a reversal of the comeback factor (CF), a measure of how unlikely a given win was.  You can click on the link for a fuller explanation, but for the purposes of this article, just know this: a CF of 20 indicates a team's lowest win probability during the game was five percent.

So using this "five-percent rule," we can do the opposite exercise, and take a look at the teams with multiple "big comeback" wins within a season, including the playoffs.  Examining the blown-game article, it was interesting that most of the teams were mediocre, with a few especially bad teams and a few very good ones.  But excluding the 2013 Bucs and Texans, the average number of losses was 8.5, the definition of average.

That's not really the case with the comeback teams.  As you might expect, these teams are a little better, as 14 of the 24 comeback squads made the playoffs (I've excluded 2012 and 2013 data from the table, since we obviously don't know how this year will finish yet).  However, unless a team had one of the two signature quarterbacks of this era, they were almost certain to regress the following season:

Sunday's Numbers Have Been Crunched

Sunday's numbers are now available, including advanced stat box scores, top players of the week, team stats, and season leader boards.

Advanced stat box scores
Top QBs of the week
Top RBs of the week
Top WRs of the week
Top TEs of the week
Top Defenders of the week
Advanced team stats
Offensive player season leaders
Defender season leaders
Team Viz
Position Leaders Viz
QB Viz
RB Viz

Philly Finishes Strong

Up 27-13, the Eagles stopped Green Bay on a 4th-and-4 from the PHI 7-yard line - a huge stop, keeping it a two-score game. But, with a full 9:32 remaining in the 4th quarter, the Packers still had plenty of time to get back in it... or so they thought. The Eagles took over on downs, deep in their own territory. What followed was a masterfully orchestrated, 16-play, 70-yard drive that drained the entire contents of the game clock.

Here we can see the development of the drive using our Markov model:

Did Marvin Lewis Make the Right Call on 4th Down in OT?

After a freak Hail Mary TD to tie the game, Cincinnati won the coin flip to start OT and drove to the BAL 33. Facing a 4th and 2, Lewis decided to for the conversion rather than attempt a 51-yard FG or punt.

Under the old sudden death OT rules, every coach would have undoubtedly attempted the FG in that situation. But under the new OT format, things have changed. Because the opponent gets an opportunity to match a first-possession FG, or to trump it with a TD, long FG attempts are not the percentage play.

If you make it, you've given your opponent all four downs to cruise down the field to respond. Plus, there is no urgency like in other four-down desperation drives because the clock is not a factor. And if you miss the FG, you've given the ball to your opponent in decent field position while triggering sudden death rules. Now, an opponent FG would end the game.

Roundup 11/9/13

Jason uses our EPA model to assess red zone pass locations. Excellent analysis. Excellent visualization.

Keith's efficiency leaders through week 9.

Chase gives us a report on "sack factor."

An update on team injury report calibration. Questionable and Probable designatees play more often than expected.

GB's playoff chances depend on Rodgers returning for the Thanksgiving day game vs DET.

Novel idea for restructuring MLB.

Podcast Episode 8 - Wayne Winston and Jeff Sagarin

Dave talks with Jeff Sagarin and Wayne Winston about their four decades of work in the field of sports statistics. Wayne and Jeff met while studying together at MIT and have been friends ever since. In the early 80's, they had their first collaboration on a football play-calling project for Indiana University's head football coach, Sam Wyche. Since then, Jeff has been publishing his team ratings in USA Today while Wayne published his book, "Mathletics", and currently teaches at Indiana's Kelly School of Business.

During the show Jeff and Wayne discuss the history of their friendship, from playing dice based football board games in their dorm rooms to their current work as professional statisticians. Jeff gives his thoughts on how the BCS computer rankings have changed in recent years while Wayne shares his ideas on how to best evaluate football teams and individual players. Questions from Twitter are also answered during the episode, so make sure to keep the ideas coming!

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Playoff Clarity

Sam Waters is the Managing Editor of the Harvard Sports Analysis Collective. He is a senior economics major with a minor in psychology. Sam has spent the past eight months as an analytics intern for an NFL team. He used to be a Jets fan, but everyone has their limits. 

The NFL season might only be nine weeks old, but the league’s playoff picture is already starting to gain clarity. Having a playoff picture that is too clear, too early, might make games a little less exciting, so I thought it would be interesting to see if this year’s playoff qualifiers really are more certain at this point than in past years.

We can start to attack this question using the projections at nfl-forecast.com, which use the team efficiency ratings here at Advanced NFL Stats to estimate each team’s chances of making the playoffs. According to these projections, eight teams currently have a probability of playoff qualification higher than ninety percent. While these teams (like Denver, Kansas City, and Seattle) are virtual locks, we have thirteen teams with a ten percent chance or less of qualifying, leaving us with a pretty polarized distribution of playoff odds after nine weeks of play:

Playoff Projections - Week 9


All of the numbers below come from Chris Cox at NFL-forecast.com. His app uses the win probabilities from the ANS team efficiency model to run a Monte Carlo simulation of the remaining NFL games thousands of times. Based on current records, our estimates of team strength, and knowledge of the NFL's tie breaking procedures we can come up with some pretty interesting predictions of how each team will fare come the end of the season. If you want to use a different model or just fiddle with the numbers by hand, go ahead and download the app yourself.

Chicago at Green Bay, Week 8's biggest game

This game turned out to be even more important than we said it would be last week. Chicago's victory gave them a 23% boost in their playoff chances, and perhaps just as satisfying for Bears fans, dropped Green Bay's odds by 19%. The division title is much less secure now, with both the Lions and Bears within reach of that top spot.

Game Probabilities - Week 10

Game probabilities for week 10 are available at the New York Times. This week I take a quick look the changing of the Guard in the AFC North.

The model has not been a fan of the Ravens, even during last season prior to their playoff run to a Super Bowl victory. This season, the model says Baltimore's "true" winning percentage is 0.333, which isn't far off from their actual 0.375 mark (3-5), particularly considering they've had a slightly soft schedule. The Ravens' passing efficiency differential is -0.5 yards per pass play, which is 22nd in the league. But their biggest problem is a costly inability to run the ball. The Ravens offense is last in yards per carry, and is a distant last in run success rate...

Note: In my write-up, I mistakenly said CIN hosts Baltimore. It's actually the other way around. The game probability numbers are correct though.

Team Efficiency Rankings: Week 9

Just because a team places in the top half of these rankings does not necessarily signify a legitimately good squad.  With only 12 playoff teams, the NFL is better at sussing out the mediocre Bucks- and Islanders-types of teams that sneak their way into more forgiving playoff structures, but the 16-game schedule lends itself to some fluky postseason participants.  Last season, the 24th-ranked Colts and 19th-ranked Ravens both made their way into the dance, though things turned out OK for Baltimore.

This season, there is one team in particular whose peripherals scream "Fluke!", yet their recent history screams "Contender!".  After wallowing in the bottom half of these rankings for the entire first half, they were this weeks biggest movers, rising seven spots to move into 10th.  But ignoring the past decade, should we really take them seriously?

Trestman's 4th and Inches Call

I received a few requests to analyze Marc Trestman's decision to go for it on 4th and inches from his own 32, up by 4 with 7:50 to play in the 4th quarter. So here goes:

Punting would hand GB the ball at or around their own 20 yard line, worth 0.71 WP for CHI.

A successful conversion means a 1st and 10 at CHI's own 33, which would give CHI a Win Probability (WP) of 0.79. And a failed conversion attempt gives GB the ball at the CHI 32, worth 0.51 WP for CHI. [That's a relatively high-leverage situation--a potential swing of 0.28 WP.]

The break-even conversion probability (x) required to make it worthwhile to go for the conversion can be found by setting the value of the punt equal to the total value of the conversion attempt:

The 2013 Buccaneers Really Know How to Blow It

This post at Reddit noted that the 2013 Buccaneers have blown 4 games in which they had at least a 0.95 Win Probability (WP). This is the most blown games for any team since at least 1999, and there are still 8 games left to blow this season.

Most readers are familiar with the Comeback Factor (CBF) stat. It measures the unlikelihood of the win at the lowpoint of the game for the eventual winning team. For example, if a team comes back to win from a 0.05 WP, that would be a CBF of 20 (1/.05 = 20). A team that comes back from a 0.01 WP earns a CBF of 100.

On the flip side of that equation is the Blown Game Factor (BGF), a stat which measures how badly a team blows a game. If a team has a 0.95 WP and goes on to lose, its BGF is a 20. It's really no different than Comeback Factor--it's just measured from a different perspective.

TB already has 4 games with a BGF of 20 or higher, meaning at one point they had at least a 0.95 WP. The table below lists all the teams in the database (since 1999) with 2 or more games with a BGF of at least 20. That's not the only way to measure total heartbreak, so I included some other numbers.

Sunday's Numbers Have Been Crunched

Sunday's numbers are now available, including advanced stat box scores, top players of the week, team stats, and season leader boards.

Advanced stat box scores
Top QBs of the week
Top RBs of the week
Top WRs of the week
Top TEs of the week
Top Defenders of the week
Advanced team stats
Offensive player season leaders
Defender season leaders
Team Viz
Position Leaders Viz
QB Viz
RB Viz

Frazier's Fourth Down Decision & Walsh Misses Wide

As 8.5 point underdogs, the Vikings managed to not only stay in the game with the Cowboys, but hold a lead with the ball nearing the end of regulation. Up 23-20, Christian Ponder faced a 4th-and-5 from the Cowboys 36-yard line with 3:04 remaining. While we are almost always a proponent of going for it in no-man's land, this presents an interesting decision point. Dallas had two timeouts remaining and with a conversion, Minnesota would be able to milk a good portion of the clock. With a made field goal from Blair Walsh - one of the top kickers in the league, despite his earlier missed extra point - the Vikings win probability actually falls to 75%. We have talked about this previously, being down six is sometimes better than being down three.

Great Offenses > Great Defenses Visualized

A few weeks back I wrote about how the distribution of team offensive production is measurably wider than team defensive production. Although I've written about the phenomenon a few times over the years, it never hurts to apply newer and better analytic tools to the question.

I had produced this histogram to illustrate the comparison between offense and defense, but the format doesn't mesh very well at NYT. For those not familiar, a histogram plots the frequency of occurrence of various levels of a variable. In this case it's a plot of team total Expected Points Added (EPA) for the 2000-2012 regular seasons. For example, there were 62 defenses (the lighter plot) that totaled between 10 and 35 EPA for a season. And there were 43 offenses that totaled the same amount.

Roundup 11/2/13

What if MLB played an NFL-style schedule? Helmet knock-Tango.

Although I sometimes use Vegas numbers as a benchmark, I don't pick against the spread. I just doesn't interest me. But I know a lot of our readers do. If so, beware of guys like me. Also beware of small sample analysis.

Scott from Football Outsiders uses WPA to evaluate for Calvin Johnson's case to be MVP. ($)

Keith's efficiency numbers underscore Johnson's case.

We have a Doug Drinen sighting! Doug devises a stat for moral victory.

Separating Receiver from Quarterback: A Start

Ty Aderhold and David Freed are second-year members of the Harvard Sports Analysis Collective. Ty is a sophomore majoring in History and Science with a minor in Global Health and Health Policy, and is a big fan of all Atlanta sports teams (proving Atlanta sports fans do actually exist). David is majoring in applied math (focusing on economics) and minoring in statistics. He is currently looking for a vintage Vince Carter Raptors jersey.

One of the biggest stories from Sunday was Calvin Johnson’s monstrous 329-yard receiving day, which prompted teammate Reggie Bush to call him “the greatest of all time” after the game. By contrast, because it came in a win, Tom Brady’s 116-yard performance went under the radar. Johnson’s big day and Brady’s less-than-stellar one prompt questions about the relationship between a quarterback and his top receiver.

One of the central figures in this debate is Matthew Stafford. For almost his entire NFL career, many have considered him a quarterback that relies on Johnson for his success. Stafford’s recent struggles in the Lions’ Week 5 game against the Packers in which Johnson didn’t play only added credence to this theory. At the same time, Tom Brady has been regarded for years as a superstar quarterback that can generate above average stats for otherwise pedestrian receivers. Many considered it to be Brady that made Wes Welker great, not the other way around. However, it has been apparent throughout the season, as it was against the Dolphins this past weekend, that Brady is suffering from a lack of talented receivers (and, potentially, an undisclosed injury). This post takes a step towards separating the value of a quarterback from his top receiver so we can better compare quarterback play across the league. It will also take an in-depth look at Matthew Stafford and Tom Brady with the goal of better understanding these quarterbacks and their successes with the likes of Calvin Johnson and Wes Welker.

To begin separating out the value of a quarterback from that of his top receiver, we looked at the best quarterback from each team in 2012 and his top receiver (defined as the receiver who gained the most yards). We also limited our data only to games that the quarterback and receiver played together. After computing the raw quarterback ratings for each quarterback, we subtracted those plays on which he targeted his best receiver and recalculated his statistics.


The Worst 8 - 0 Team of all Time?

CBS's Pete Prisco recently sent out a tweet saying the Chiefs "might be the worst 8 - 0 team I've ever seen."  I thought I would take him up on that by compiling some basic team stats of every 8 - 0 team in a Google spreadsheet and comparing them.

Regardless of what the stats say, you should familiarize yourself with this amazing gif which is probably the only reason the internet needs to exist and is proof-positive that Andy Reid's Chiefs are worth every bit of 8 and OHHH YEEEAAAA.

The spreadsheet will contain the following stats on each team: