[Ml-stat-talks] Wed 5/15: Shane Jensen ranks the NHL

David Mimno mimno at CS.Princeton.EDU
Fri May 10 11:48:10 EDT 2013

For our last ML talk of the semester, we welcome Shane Jensen from Penn.
Shane has many outstanding achievements, but the best may be having his
previous work on baseball called "junk science" by the New York Post. Find
out about the issues involved in measuring individual performance in team
sports, and whether he owes Derek Jeter an apology!

Wed May 15, 12:30, CS402

Estimating player contribution in hockey with regularized logistic

Shane T. Jensen
Department of Statistics
The Wharton School
University of Pennsylvania

We present a regularized logistic regression model for evaluating player
contributions in hockey. The traditional metric for this purpose is the
plus-minus statistic, which allocates a single unit of credit (for or
against) to each player on the ice for a goal. However, plus-minus scores
measure only the marginal effect of players, do not account for sample
size, and provide a very noisy estimate of performance.  We investigate a
related regression problem: what does each player on the ice contribute,
beyond aggregate team performance and other factors, to the odds that a
given goal was scored by their team? Due to the large-p (number of players)
and imbalanced design setting of hockey analysis, a major part of our
contribution is a careful treatment of prior shrinkage in model estimation.
We showcase recent developments for posterior maximization and simulation
in this setting.  Our results show that most players do not stand out as
measurably strong (positive or negative) contributors. This allows the
stars to really shine, reveals diamonds in the rough overlooked by earlier
analyses, and argues that some of the highest paid players in the league
are not making contributions worth their expense.   This is joint work with
Bobby Gramacy and Matt Taddy at the Booth School of Business, University of
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