The State of Analytics: Too many soccer analytics posts lack Statistical Power

“I mentioned at the start of these columns I know next to nothing about even basic statistical science, but it appears if I or indeed any of us are going to help in moving forward on developing useful metrics in gaining a better understanding of best practices in football, that might have to change. The reason is that one of the major misunderstandings among amateur soccer analytics writers is the importance of Statistical Power, generally determined by an accurate and useful sample size. The name of the game is eliminating the possibility of Type I and II errors, which involve ruling out a null hypothesis (no statistical correlation between factor X and result Y).” The Score (Video)


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