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Sports Performance Measurement and Analytics: The Science of Assessing Performance, Predicting Future Outcomes, Interpreting Statistical Models, and Evaluating the Market Value of Athletes by Lorena Martin

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4. Selecting Statistical Models

“Statistics are like a bikini. What they reveal is suggestive, but what they conceal is vital.”

—AARON LEVENSTEIN

As a data scientist, not only are you required to understand the sport, the players, and the performance data, but also how to convey this information to decision makers such as management and operations personnel. A crucial step which lies between understanding the performance data and the decision-making process is the selection of statistical and predictive models for optimal analysis.

Aside from generating hypothesis- or data-driven analyses, it is up to you to present the results in a meaningful metric to management. For instance, although we may be excited about p-values, standard errors, and ...

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