Quote:
Originally Posted by tschock
To put it another way: If a statistician's model is good at analyzing the past, then it should be reasonably good for predicting the future. Otherwise your model needs adjusting to consider other factors. That didn't seem to play out very well when 'the best team in baseball' this year didn't even get close to winning the World Series (as one example).
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Dead on!
If you go back and read an earlier post in this thread it was stated that sabermetrics and statistical analysis was basically developed for gambling purposes. Well that is only for predicting games between two teams today. And over time, statisticians could tweak and refine those as they'd actually get to see how well it predicted the winner of a game. But there is no outcome or winner when you try to use statistics to decide the best lefty of all time. The formulas being used don't predict anything, and there is no winner decided that allows you to prove your formula was right, or to tweak your statistical formula if it was proven wrong. Statisticians just use the numbers they pull directly from baseball, ignoring outside and human influences, and interpret those stats in how they feel they would. The stats and formulas are nothing but talking points, as they can't prove or disprove anything regarding who really was the best. You can interpret the numbers how you want.
And they are certainly not infallible for gambling purposes either, as they don't always pick the winner.