Referee Efficiency Ratings
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There’s not 10 players on the court, there’s 13. And three of them determine about 80 percent of what happens out there.
Along with this excerpt, he mentioned something along the lines of: “so if you’re not looking at the refs then you’re missing out on a lot.”
The point I get is, if we don’t understand refs, then we don’t understand the game.
With this, he makes a very good point. I think Mark gets a bad rap for wanting to talk about refs, when in reality we should be talking about refs. With all of the on/off-court work we’re doing, refs seem to be an obvious component to add. They absolutely are on the court. And they’re on the court a lot.
So why, then, have we not been looking at refs? I can come up with a few quick reasons:
- Refs don’t get credit for points in the box score, so ESPN doesn’t highlight their contributions on SportsCenter.
- Your favorite team can’t sign and/or trade refs.
- We don’t give MVP awards to refs.
- Refs don’t dunk or hit the game winning shot.
There are certainly many more, I bet, but that really isn’t the point of this post.
The point of this post is to measure the relationship between referees and efficiency.
To measure this relationship, I fit the following model to data from the ’07-’08 season:
Efficiency = Intercept + HCA + O1 + … + On + D1 + … + Dn + R1 + … + Rn
Where Efficiency = Points Scored per 100 Possessions, the home court advantage HCA = 1 if the offensive team is at home, O1,…,On = 1 if the player is on offense, D1,…,Dn = 1 if the player is on defense, and R1,…,Rn = 1 if the referee is on the court. These variables are 0 otherwise.
The following spreadsheet lists the referee ratings:
The following spreadsheet lists the offensive ratings:
The following spreadsheet lists the defensive ratings:
Interpreting the Results
To interpret these results, we want to think in terms of holding all of the other variables at some constant value. As an example, for the refs, we’d estimate that Derrick Stafford is associated with an increase in 7.8 points per 100 possessions he’s on the court.
That being said, what would we want a ref’s measured relationship be? In my mind we’d want their relationship to be 0, as this would indicate the referees all have the same relationship to efficiency. Based on these results, I think it’s safe to say this is not the case. I’m sure Mark Cuban would agree.
The astute reader will notice all of the refs have standard errors that indicate the coefficients are not statistically significant from 0. Thus someone might conclude refs (or coaches, for that matter) don’t have an impact. But given our knowledge of the game and these results, it is safe to say that these refs do not call everything the same way.
A final point to mention is that there are always 3 refs on the court at one time. Thus their combined impact is not likely to be 0. That being said, it might be worth treating refs as individual units to see what sort of relationship ref units have with efficiency.
What Things do Refs do Differently?
Just like player ratings, this model doesn’t tell us why this relationship exists. It doesn’t tell us what refs are doing differently from each other, it’s just telling us there is some difference.
In an attempt to quantify this sort of thing, I’ll be including refs in all of my future on/off-court work. Hopefully this will give further insight into the differences between refs.
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