Text Mining and Improving NHL Draft Analytics

Combining performance data (“stats”) and scouting information is the Holy Grail of sports analytics. In this paper, we develop a methodology to combine scouting report information with performance metrics to improve the evaluation of players eligible for the NHL Entry Draft. In this new approach, text-mined data from scouting reports was used to develop variables for out-of-sample prediction. We demonstrate that by adding these variables to performance metrics, we can substantially improve the prediction of future performance.

Below is a paper that we (Timo Seppa, Michael Schuckers and Mike Rovito) recently wrote on NHL Draft Analytics entitled Text Mining of Scouting Reports as a Novel Data Source for Improving NHL Draft Analytics.  

Here’s a link to the paper: ¬†TextMiningScoutingNHLDraftAnalyticsFeb2017

Timo will be presenting this work at 2017 Ottawa Hockey Analytics Conference #OTTHAC17 on May 6th.

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