Team Efficiency Rankings - Week 10

Week 10 already. The season seems like it's flying by. The biggest mover this week is PHI. They started the season high on the rankings. Their defense looked very strong, and their offense was moving the ball. The only thing holding them back was turnovers, which tend to regress very strongly. Well, they haven't in PHI's case, meanwhile their pass protection has collapsed and their defense has regressed to league average.

CAR is still the mystery team, so let's take a quick look at why a 2-win team is ranked 4th. They have the 4th most efficient passing offense, league-average run success rate, and a better than average offensive turnover rate. They have an above average defense, ranked 11th in both the run and pass--which makes them much better than 11th, by the way. Plus, CAR has a slightly better than average penalty rate. Add in that they've faced the 4th toughest schedule so far, and they look like a team that should win nearly 2 out of every three games.

Here are the efficient rankings for week 10. Click on the headers to sort. The efficiency components of the model are in the second table below.

Four 4th Down Decisions: Steelers Go Strictly on Feel

Big Ben and Eli Manning faced off against each other Sunday, leading the teams that have won four of the last seven Super Bowls; Manning and Roethlisberger will always be linked as the No. 1 and No. 3 QBs taken in the 2004 NFL draft. Let's look at the plethora of interesting decisions between the coaches.

What first tickled my fancy was when the CBS announcer mentioned that, "Mike Tomlin says he makes all these decisions strictly on feel." This was before the Steelers went for it on 4th-and-1 from the Giants 48-yard line, down 7 in the second quarter. After I shuddered at the quote, I checked out the 4th-down calculator to confirm my notion that this was one of the easier football decisions to be made:

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
• QB Viz
• RB Viz

Analytics and the Ludic Fallacy

Analytics have become a major part of political campaigns. Candidates now employ a large number of analysts who find every point of leverage possible. They target potential voters in ever narrowing slices, matching messages containing certain styles and emphasis with particular demographic audiences.

One of the most visible applications of analytics in this year’s election is the FiveThirtyEight blog, created by Nate Silver. For those who may not be familiar with Nate, he is a noted baseball sabermetrician best known for creating the PECOTA prediction model. His election forecast has favored Obama more heavily than most others throughout the election season, and he has been the target of criticism recently.

In defending his approach, Nate and others have explained his probabilistic reasoning with examples from football. The 90% or so chance Nate gives Obama to win the Electoral College is, for some reason, put in football terms…Romney is down by 3 with 2 minutes to play…or Romney is down 7 with 5 minutes to play…or something along those lines. (I think that's ironic given that even football experts don't seem have a good grasp of situational probabilities.)

I disagree with those analogies, but not because I have any better reason to think that either candidate will win. I think the situation is more like this: Romney is down by a very small number of points with 1 minute to play, and we don’t know who has the ball or where the line of scrimmage is. Or maybe it’s more like this: Romney is down by a point or two and has just snapped a long field goal attempt, and no one has a very good idea which way the wind is blowing. If it was blowing just like it was last game, the kick will almost certainly come up short. But if the wind is blowing more like it did two games ago, he’ll probably make the kick and win.

Playoff Projections - Week 9

Playoff projections are back! As always, these numbers come courtesy of Chris Cox at NFL-forecast.com and are generated with the help of his NFL-Forecast software app, which uses the win probabilities generated by the team efficiency model to create a Monte Carlo season simulation. And if you don't buy the game probabilities from Advanced NFL Stats, you can tweak them as much as you like to generate your own playoff projections. I encourage everyone to download the app and test out your own scenarios.

The Texans have the inside track in the AFC and the Falcons have it in the NFC. No surprise there. The AFC South, AFC West, NFC South and NFC West appear to be locks for the Texans, Broncos, Falcons, and 49ers. The one counter-intuitive projection is that Baltimore is not the favorite in the AFC North despite having a full game lead on Pittsburgh.

The Extra Point Must Go

This week's article at the Post asks What's the point of the extra point?

 The extra point is something left over from gridiron football’s evolution from rugby. Originally, the ‘touchdown’ in rugby was less important than the ensuing free kick, and the points given for the touchdown and the ‘point after try’ varied during football’s early history. Today’s extra point is a vestige of football’s rugby roots. It’s football’s appendix–inconsequential, its original purpose uncertain...and safe to remove.

Weekly Game Probabilities

Game probabilities for week 9 are up at the New York Times' Fifth Down.

This week I look at what's wrong with the Steelers defense.

Which Teams Should Run More?

If I read one more of these articles in the Baltimore Sun, I think I'm going to throw up.

...Ray Rice consistently ranks as one of the most productive and dynamic running backs in the NFL, capable of eluding defenders on the ground and through the air. He benefits from running behind bruising All-Pro fullback Vonta Leach, who's regarded as the most devastating lead blocker in the game. Yet, the Ravens have fallen to 19th overall in the NFL in rushing yards per game with an average of 104 yards per contest. And Rice ranks 12th on the rushing chart individually with 524 rushing yards...

The article goes on to add:

Blah blah blah. Run more blah. Need to find their identity blah blah.

Ok, I made that second part up. Actually, I have to give the author credit for attempting at least a surface level statistical analysis. But the fetish that sports columnists have with the running game has been one of the most enduring false narratives in the sport of football. It's time to put it to rest. I get that offenses have to run to keep defenses honest and to set up the passing game, but they don't have to run as often as they generally do to accomplish those things.

Let's take a look at offensive Expected Points Added per Play by play type. EPA/P accounts for all play outcomes--sacks, interceptions, fumbles, gains, losses, first down conversions, and so on--in other words, everything. Naturally, an offense would want to do more of the kinds of plays that gain them more and do less of the kinds of plays that gain less. Although this should be intuitively understood, zero-sum game theory proves that the optimum total production is when payoffs are equalized across strategy options.

Teams with high differences between pass payoffs and run payoffs should probably be running more often. And although you might think that teams with higher run payoffs than pass payoffs should be running more, that may not be true due to the passing paradox: Underdog teams that are poor at passing may need to do it more often to generate high variance outcomes.

The table below lists each offense's passing and running EPA per play, their total EPA per play, the difference between pass and run EPA/P, and their proportion of pass plays. I limited the analysis to 'normal football' where the score is relatively close and time is not yet a factor in play selection. The teams are ranked by the difference between pass and run payoffs. Teams at the top of the list should be passing more, and the teams at the (very) bottom should be running more. (Click on the table headers to sort.)