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Predicting the Schedule: Statistical Speculation!

Statistical Goodness!

As you all might know, I’m a bit of a geek. Numbers and analysis make me increadably giddy inside, as I like knowing that there’s a little bit of science behind the punditry, rather than just the ESPN garbage that we’re used to. Normally my default for this sort of insight are the fine folks at Pro Football Reference and Brian at NFL Stats has put together some awesome analysis for you to ponder.

Here's a little taste of his insights about what makes a team win.

RUN AND PASS EFFICIENCY

How often have you heard an NFL commentator say, "When running back X gets at least Y carries, his team wins?" The clear implication is that the team in question should feed a steady diet of carries to the running back, and this will cause his team to win. What if we stated the same observation this way, "When his team is winning, running back X receives at least Y carries?" And by the way, why don't we ever hear, "When QB X passes at least Y times, his team wins?" Here's why:

Stat            Win Correlation
-----------------------------------
Rush Attempts         0.58
Pass Attempts        -0.17

The negative correlation for pass attempts means that the more often a team passes, the less likely it is to win. The correlation of rush attempts with wins (0.58) is even stronger than that for total rushing yards (0.45). This is a curious result, and it's where conventional NFL analysis begins to crumble.

When we see two things that appear correlated, it is natural for us to say that one causes the other. The runs come during the game, and the win comes at its conclusion. Therefore most fans and analysts assume the running causes the winning. The problem is, it usually doesn't. It's the winning that causes the running. Teams that are ahead, and likely to win, run the ball to take time off the clock and to minimize the risk of a turnover. Teams that are behind, and likely to lose, abandon the run in favor of the pass. Statistics can measure the correlation, but it can't determine the direction of causation.

The critical question then becomes: how can we truly measure a team's passing and running abilities and their respective contributions to winning? The answer is football's equivalent to the batting average--efficiency stats. If we want to know how good a team is at running, the best way is to know how many yards it tends to gain each time it runs the ball--yards per rush attempt. The table below lists basic passing statistics and their correlation with season wins.

Stat            Win Correlation
--------------------------------
Pass Yards             0.31
Pass Attempts         -0.17
Pass Yds/Att           0.61

Yards per pass attempt is merely pass yards divided by pass attempts. So we have a relatively weak statistic (0.31) divided by an even weaker one with a negative correlation with winning (-0.17). We would expect to have a fairly meaningless result, but we don't. Passing efficiency turns out to be strongly correlated with winning (0.61). And unless having a lead in a game `causes' a team's passes to be more successful, we can safely say that passing efficiency leads to winning.

Because sacks are an important factor in the passing game, I include plays that result in sacks as pass attempts for the purpose of calculating efficiency. Likewise, I also subtract sack yards from total passing yards. I call this true pass efficiency and have found it correlates better with both offensive points scored and wins.

If you're like me, you want to know what he thinks the Jaguars will do this year.  Brian has it all under control with his 2007 predictions   Before explaining the chart I've posted here, let's look at his methodology.  Brian uses a Logit Regression using efficenicy statistics from 2006.  He claims to get a 68% success rate from using this method, and his numbers versus Vegas back that up.

Ok, so what does this chart mean.  Each "bar" represents the probability of a team winning that many games.  In Jacksonvilles case, we have a slightly better than 1% chance of winning 15 games, a 15% chance to win 12 games, 21% chance of 11 games, and 22% chance of 10 wins.  Of course, there is also a 1% chance of a 5 win season, which would cause me to melt down and die.

The predictors indicate the AFC South most likely ending up like this

IND 11
JAX 10
TEN 6
HOU 5

Under this situation the AFC playoffs would feature SD, BAL, PIT, IND, NE, and JAX.

Not a terrible outcome if you ask me, I'd like to see Jax and Indy be within a game of each other for the division, that'd be pretty frigging awesome.

Anyhow, do yourselves a favor and check out this site.  I'm going to see if I can get in contact with him and look a little closer at the Jags.

-Chris