This review focuses on the usage of machine learning methods in sports. It closely follows the PRISMA framework for writing systematic reviews. We introduce the broader field of using sensor data for feedback in sport and cite similar reviews, that focus
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To perform this analysis, the first step was to transform the raw data responses into fuzzy set responses by removing all missing data. Prior to the analysis, the condition values were recalibrated to have values between 0 and 1. To calibrate the continuous variables (variables with more than ...
the spectator ever closer to the play. Electronic sports will move far beyond today’s relatively passive viewing when homestadiumand virtual-reality technology are introduced. The first will allow viewers to make their own production choices of camera angle and displayed sports data; the second ...
Obtaining data on social outputs for sports clubs involves tapping into a mix of internal records, public sources and partnership data. Some studies check robustness of the results by estimating efficiency with different input–output sets (e.g., see [33]). We do not do this). Figure 2. ...
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Emotional discipline cannot be understated. Betting decisions should be driven by logic and data rather than emotion. Here’s how to maintain a disciplined approach: Have a pre-set strategy and stick to it, even when faced with losses. ...
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assessed in the study. However, the actual measurements (e.g., mean, standard deviation) derived from specific tests (e.g., 30 m linear sprint) were not extracted. All data (i.e., study characteristics and dependent variables) were coded into a specifically designed Microsoft®Excel ...
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