Overview and Analysis of FIRST Stats

[AGPapa]

Originally Posted by wgardner

In Plot 5, the performances of the different techniques get close to each other as the tournament nears completion. They should all converge as the number of matches grows large as the LS and MMSE solutions will eventually converge to each other. But they are off by quite a bit early on. Even though the MMSE 1 solution with Var(N) underestimated at 1*Var(O) is underestimating the Var(N), it still gives pretty good results.

Thanks Will, the fact that even choosing a bad value for Var(N) gives decent results alleviates a lot of my concerns about searching for Var(N) and Var(D) after the fact.

It’s also impressive at how much better MMSE techniques are for when an event is underway and not a lot of matches have been played. This is helpful for predicting the outcome of the second day of matches (and thus seeing who is likely to be a captain).
Is this behavior typical for all stats or just OPR? Could you run a similar plot for sCPR? (since that stat seems to do slightly better than OPR).


Additionally, how would you implement the techniques described in the “Advanced MMSE Estimation” section? What would you change in the pseudocode to, for instance, change a team’s apriori Oi?