Blog Archives

Winning the QMJHL Draft with Advanced Predictive Modeling

Can a numbers-based approach outdraft QMJHL teams? I spent the last year trying to build an advanced predictive model to see if this was possible. As a test, I did a re-draft of the 2013 draft, since the majority of those players finished their QMJHL careers this season. Using exclusively information that was available before the draft and without taking into consideration any subjective factors (scouting, interviews, team needs, etc.), my model outdrafted every single team in the 2013 draft in terms of drafted player value (APV)

Tagged with: , , , , , , , , , , ,
Posted in APV Analysis, Draft Analysis

Introducing APV – A Single-number Player Evaluation Metric

APV scores go from 0 (negligible positive value) to close to 1000, with the league average being 100. Any player with a score above 100 is generally considered “above average”, and less than 100 “below average”.

Tagged with: , , , , , , , , , , , ,
Posted in APV Analysis
Follow on Twitter