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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Sports Analytics Methods – Hawk Eye Data

This is a review of the Hawk-Eye Electronic Line-Calling System Data research conducted by Simon Choppin, Simon Albrtecht, James Spurr, and Jamie Capel-Davies. As technology has improved, the ability to analyze the game of tennis has been enhanced.  One such technology is the Hawk-Eye Electronic Line-calling System.  This system automatically tracks the ball and players…

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Sports Analytics Methods – Allocative Efficiency and Dynamic Efficiency

This is a review of the basketball research applying allocative efficiency and dynamic efficiency techniques conducted by Brian Skinner and Matthew Goldman. The end goal for any basketball game is to win the game.  In order to maximize the chance of winning, teams need to evaluate the effectiveness of their strategies in influencing the outcome…

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Sports Analytics Models – Bipartite Graph Algorithms

This is a review of the NBA research using bipartite graph algorithms conducted by Sohum Misra. Basketball is ever growing in its popularity.  Teams look for new techniques to help them gain advantages over their competitors.  One technique increasing in its use is advanced statistics.  These statistics help teams determine the intangible value of an…

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Sports Analytics Methods – Injury Risk Mitigation System (IRMS)

This is a review of the Injury Risk Mitigation System (IRMS) research conducted by Calham Dower, Abdul Rafehi, Jason Weber, and Razali Mohamad. Player injuries are a key concern for all teams across all sports. Injuries can cost teams thousands of dollars every day and negatively affect the teams’ competitiveness. Over the years several programs…

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Sports Analytics Methods – Spatiotemporal Trajectory Clustering

This is a review of the spatiotemporal trajectory clustering soccer research conducted by Jennifer Hobbs, Paul Power, Long Sha, Hector Ruiz and Patrick Lucey. In soccer, transitioning from defense to offense and vice versa is extremely important. However, there are no methods to quantify or rank the effectiveness of these transitions. In order to create…

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