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Activity Number: 154 - Sports Analysis: New Insights
Type: Topic Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Sports
Abstract #329593 Presentation
Title: The Hot Hand Theory in Hockey: a Multilevel Logistic Regression Analysis
Author(s): Likang Ding* and Armann Ingolfsson and Ivor Cribben and Monica Tran
Companies: and University of Alberta and University of Alberta and University of Alberta
Keywords: Hockey; Hot Hand theory; logistic regression; multilevel regression

The Hot Hand theory states that an athlete will perform better in the present if he/she has performed well in the recent past. This theory has been investigated for basketball, baseball, and other sports. We test this theory for National Hockey League (NHL) playoff goaltenders by estimating how their performance on recent shots influences the probability of saving the next shot on goal. We use multilevel logistic regression models, in which we allow either some or all coefficients to vary among the season-goaltender combinations. Our data consists of 48,431 shot-on-goal observations for 93 goaltenders who played in the NHL playoffs between 2008 and 2016. Our preliminary findings are that a good recent save performance has a negative effect on the save probability for the next shot, which is consistent with the opposite of the Hot Hand theory.

Authors who are presenting talks have a * after their name.

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