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Data science used for player analysis

To improve performance, players keep track of their own statistics and analyze how they played in previous games. Nutrition, training hours and game performance produce different types of statistics, such as how fast the player runs, how much weight they lift, or how much protein they ate during the day.

By tracking this data and comparing it to how they felt on game day or how they performed, players can make changes to their training routines or diet to get better at their sport. When all players focus on their own performance analytics and pinpoint how to improve, this analysis and the changes that come with it help prevent organizations from becoming the most disappointing sports team in the league.

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Updated 2020-12-14

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Data science references

Data Science