WIN PROBABILITY GRAPHS

Check out the Win Probability graphs and play-by-play of your favorite team's biggest comebacks and most exciting games since 2000. An explanation can be found here. Just select a year, a team, or 'any', and start clicking:

Or search for all the games for your favorite team:

Or browse the current season by week:

Nov 12, 2009

Game Probabilities - Week 10

Weekly game probabilities are available now at the nytimes.com Fifth Down.


Nov 10, 2009

Efficiency Rankings - Week 10

The team rankings below are in terms of generic win probability. The GWP is the probability a team would beat the league average team at a neutral site. Each team's opponent's average GWP is also listed, which can be considered to-date strength of schedule, and all ratings include adjustments for opponent strength.

Offensive rank (ORANK) is offensive generic win probability, which is based on each team's offensive efficiency stats only. In other words, it's the team's GWP assuming it had a league-average defense. DRANK is is a team's generic win probability rank assuming it had a league-average offense.

GWP is based on a logistic regression model applied to current team stats. The model includes offensive and defensive passing and running efficiency, offensive turnover rates, defensive interception rates, and team penalty rates. If you're scratching your head wondering why a team is ranked where it is, just scroll down to the second table to see the stats of all 32 teams.


The Value of 1st Down and 5 Situations

In a recent post I illustrated how to decide whether to accept or decline a penalty based on expected point (EP) values. I compared 1st down and 5 situations, often resulting from a defensive offside, 2nd down situations.

I had to assume a roughly linear point advantage for the 1st and 5 situations because there weren't nearly as many in the data as other situations. But when I actually plotted out the empirical average EP values for 1st and 5s and each yard line, I noticed something strange. Compared to the curve of 1st and 10 values (for which there is an abundance of data), the curve of 1st and 5 EP values was oddly shaped. As we'd expect, there is a fair advantage for 1st and 5s from a team's own 20 through the opponent's 45 or so. But from there all the way to the opponent's 5, the value of a 1st and 5 is apparently lower than that for a 1st and 10.


Nov 9, 2009

Second-Guessing Coughlin and Reid

Toni Mokovic at Fifth Down questions the late-game decision-making of Tom Coughlin and Andy Reid in their respective losses Sunday. Let's see what WP says.

The Giants had an opportunity to put away the Chargers with a touchdown to put the game out of reach. They went conservative, opting for the FG and a 6 point lead. The lead didn't hold up as the Chargers were able to drive for a game-winning TD.

After suffering a penalty on 1st down, the Giants had a 1st and goal from the Chargers' 14 yard line. After a run and a pass for no gain, the Giants faced a 3rd and goal from the 9. Run plays on 3rd and goal from from the 9 are TDs 13% of the time, while pass plays are TDs 20% of the time. Passes from there are intercepted about 4% of the time.


Accept or Decline: 1st & 5 vs 2nd & Short

Your team has just run the ball for a hard-fought 8-yard gain on 1st down bringing up a 2nd and 2. The defense was flagged for offsides giving you the option of making it 1st and 5. Should your team accept or decline the penalty or take the gain?

To simplify things, let’s only consider situations between the 20-yard lines. Looking at each option in terms of the probability of converting for a 1st down, you should be indifferent. Both situations convert equally as often at an 85% rate. But 1st down probability isn’t the whole story.


Nov 8, 2009

Another Run-Pass Balance Study

Benjamin Alamar, author of the Passing Premium paper (critiqued here), takes a second stab at comparing the values of running and passing with new research. A brief presenting his methodology and findings was presented at a recent symposium on sports statistics. This time Alamar uses expected points as a measure of value, and compares the EP values gained by passes with those of runs. He defines risk as the probability each play type will result in a negative EP change, and finds that running is both less productive and "riskier" than passing. There are three fairly big problems in the methodology. Fortunately, all three can be rectified.

First, Alamar creates his EP values using a simple linear regression (see slide 10). Using down, distance, and yardline (plus other variables controlling for quarter and other effects), he produces an EP equation. This is a really bad way to estimate EP values. They're not linear, and there are any number of interacting effects within. The Levitt-Kovash paper, in contrast, uses a regression with quintic terms and full interactions to create their EP values. (I prefer a  more direct method--looking at the data empirically and smoothing it using a method called LOESS.)


Nov 7, 2009

Roundup 11/8

A new site from the Harvard Sports Analysis Collective looks promising. (But what's with the term "Collective?" What happened to "Club?") Here they look at 2-point conversion decisions.  They also look at what effect the new wedge rule might be having on kickoff distances (not much, especially if you consider the weather is about to get a lot worse). Do teams with RB committees run better than teams with a feature back? How much more accurate are FG attempts when kicked indoors? Overall, the site asks some neat questions and is definitely headed in the right direction.

Greg Easterbrook on coaching: "One factor here is the Illusion of Coaching. We want to believe that coaches are super-ultra-masterminds in control of events, and coaches do not mind encouraging that belief. But coaching is a secondary force in sports; the athletes themselves are always more important. TMQ's immutable Law of 10 Percent holds that good coaching can improve a team by 10 percent, bad coaching can subtract from performance by 10 percent -- but the rest will always be on the players themselves, their athletic ability and level of devotion, plus luck."

I'd mostly agree with Easterbrook, however I'd say that a good coach can make a good team 10% better, but a bad coach can absolutely ruin a good team. In most cases though, the NFL rarely features coaches bad enough to do that kind of damage simply because the league is considered the top of its profession. I think the bigger point is that modern coaching, beyond the leadership aspect, is mostly about the illusion of control.