1. Predicting the NHL Playoffs Daniel Boucher Tarek Bos-Jabbar

2. How Do We Predict Who Will Win a Hockey Game?  Hockey is a fundamentally unpredictable game, lots of luck is involved.  Over an 82 game season, Winning percentage is heavily affected by luck.  We looked at predicting outcomes using more repeatable measures than wins and losses.

3. A First Attempt – Pythagorean Expectation  What decides who wins or loses a hockey game is their goals for (GF) and goals against (GA).  A useful model for W% then uses GF and GA as variables.  One of the simplest of these models is the Pythagorean Expectation.

4. Pythagorean Expectation

5. Introducing Advanced Hockey Stats  Winning or losing a game has a lot of luck involved, so does goals.  When looking for predictive value, one focusses on repeatability.  As far as repeatability is concerned, these stats are king

6. Using Advanced Stats  Three stats, Shot Attempts (Corsi), Unblocked Shot Attempts (Fenwick), and Shots, are considered Advanced Indicators of Possession  We used Fenwick to predict games as well as a regression of all three. (MacDonald, 2012)

7. Boosting r^2 with future wins  The last thing you may notice is that we boosted correlation with wins by only using the events that occurred at 5-on-5 with score close.  This has been shown to correlate better with future wins because most of a game is played 5-on-5 and drawing penalties is not a repeatable skill.  We use only close games because the score has been shown to affect possession indicators.