Sports Analytics Methods – eSports Analytics

This is a review of the e-sports analytics research conducted by Matthias Schubert, Anders Drachen, and Tobias Mahlmann. The field of e-sports, computer games played competitively, is growing around the world, with millions of competitors and millions of viewers. As a result, e-sports analytics have emerged, which relate to both sports analytics and digital game…

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Sports Analytics Models – Convolutional Neural Networks

This is a review of the convolutional neural networks research conducted by Paul Power, Jennifer Hobbs, Hector Ruiz, Xinyu Wei, and Patrick Lucey. In the English Premier League, the discrepancy between the larger market and smaller market teams grows consistently wider.  One strategy that the small market team could use to help decrease this disparity…

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Sports Analytics Models – Weighted Least Squares Regression for Adjusted Plus Minus Rating

This is a review of the Weighted Least Squares Regression Model research with NHL data conducted by Brian Macdonald. NBA analysts and teams use the adjusted plus-minus (APM) stat to determine players’ contributions to the offense and defense.  One strength of the APM is that each player’s score is not dependent on his teammates’ scores…

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Sports Analytics Methods – Expected Rewards Technique Used In Fantasy Sports

This is a review of the expected rewards in fantasy sports research conducted by Martin B. Haugh and Raghav Singal Daily Fantasy Sports is an ever-growing industry with millions of users participating each year.  DFS covers a wide variety of sports including football, basketball, baseball, soccer, and golf.  Each competitor puts together a fantasy team…

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