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Activity Number:
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243
- Statistics in Sports and Beyond
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Type:
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Contributed
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Date/Time:
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Wednesday, August 11, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Section on Statistics in Sports
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Abstract #317684
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Title:
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Predicting the Outcome of Shotokan Karate Matches
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Author(s):
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Ryan Savitz* and Olivia DiDonato
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Companies:
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Neumann University and Neumann University
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Keywords:
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logistic regression;
sabermetrics;
karate
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Abstract:
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This paper introduces a model that can be used to predict the outcome of Shotokan karate matches. This model utilizes multiple karate related variables to determine the winner of a competition in Shotokan karate. The model was constructed using logistic regression analysis and data from previous matches. The original model we constructed was refined into a more parsimonious model due to the existence of multicollinearity issues in the original model. The final model predicts the outcome of matches with 91.7% accuracy. We also utilize a subset of the variables involved in the previous analysis to construct a single statistic that may be used to capture the skill level of Shotokan karate participants.
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Authors who are presenting talks have a * after their name.
