Passing 2 - Playmaking

PLAYMAKING METRIC

A PLAYMAKING METRIC BETTER THAN ASSISTS

https://www.greaterthanplusminus.com/2013/07/play-playmaking-metric-part-1-intro.html?m=1

Our playmaking metric is based on both shots and goals.  Since shots are often more consistent than goals, and better predictors of future performance than goals, including shots helps a lot. 

We start by defining a player’s “marginal contribution”, or his total contribution to his team.  It is similar to WOWY or WOWY-like analysis

M = GFon – GFoff

In any case, you can just pretend this is WOWY,

https://www.greaterthanplusminus.com/2013/07/play-playmaking-metric-part-2.html?m=1

So we have this WOWY for every player, and we are going to decompose it into two parts, competitive contribution (Comp) and altruistic contribution (Alt). 

Alt  = WOWY – Comp

Altruistic contribution is basically the difference in the goals scored by a player’s teammates (not including the goals that the player himself scored) when he is in on the ice versus when he is off the ice.  In other words, it is a measure of how he affects his teammates’ goal scoring.  If his teammates score more goals with him than without him, he’ll have a high altruistic contribution, regardless of whether or not he scores many of the goals. 

So his WOWY is broken into two parts:

WOWY = Comp + Alt

A player’s altruistic contribution is the difference in shots taken by his teammates (not including his own shots) when he is on the ice versus when he is off the ice. If his teammates take more shots with him than without him, he’ll have a high altruistic contribution, regardless of whether or not he himself took a lot of shots. This quantity is what we’ll use, along with assists, to develop the playmaking metric.

https://www.greaterthanplusminus.com/2013/08/play-playmaking-metric-part-3-results.html?m=1

If a player’s teammates take more shots when he is on the ice versus off the ice, his altruistic contribution will be high.

We combine assists per 60 minutes and shot-based altruistic contribution (also a per 60 minute rate stat) in one half of season to predict assists in the second half of the season.  To determine the best way to combine assists and altruistic contribution, we use a multiple linear regression.  The expected assists per 60 minutes that we get from this regression model are what we call our playmaking metric, PLAY.

In all cases, PLAY was (1) more consistent than assists and (2) better than assists at predicting future assists.