Sports Analytics – Multiple Least Squares Regression w a Lagged Dependent Variable

This is a review of the NBA research conducted by James Tarlow, applying multiple least square regression, including a lagged dependent variable. Within sports, it is always assumed that experience improves a team and leads to championships. This is especially true in the NBA. Teams made up of younger players are viewed negatively for their…

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Sports Analytics Methods – Mixed-Integer Linear Programming Model

This is a review of the NFL schedules research applying mixed-integer linear programming titled “Alleviating Competitive Imbalance in NFL Schedules:  An Integer-Programming Approach“. The National Football League has a strong fan base and generates more revenue than any other sports league in the world.  During a regular season, NFL games are scheduled primarily on Sundays…

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Sports Analytics Methods – Probabilistic Graphical Models

This is a review of the basketball research conducted by Min-hwan Oh, Suraj Keshri, and Garud Iyengar applying probabilistic graphical models for basketball match simulation. With any sporting event, it is natural for analysts, bettors, and fans to make predictions regarding the outcome.  This is certainly true within the National Basketball Association. A simulation infrastructure…

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