Baseball And Machine Learning – How Baseball Helps Predict The Future?

I am a huge fan of data. It gives me solid ground and helps me be motivated – I even had an Excel Spreadsheet Experiment That Changed My Lifestyle. I’m also a huge sports geek, and I follow everything from curling to darts, from snooker to football – and during quarantine, I found the perfect brew of sports and data. Baseball. I’m not kidding here. Watching and analysing baseball in fact made me get better at forecasting – and I’m going to show you how. Data-based approach changed baseball Baseball has always been at the forefront of using data-based metrics in evaluating games or players. But until the early 2000s, baseball was a game mainly won by rich teams that could afford to buy the best players. Traditionally, as with all other sports, baseball scouts were travelling around, looking at players, determining who are gems and who are busts. But their method was flawed in a very human way. Scouts often privileged recent performances over long-term trends and relied too much on feelings and intuition over analytics. In a move known to us from the book and the Brad Pitt movie Moneyball, Oakland Athletics had decided to algorithmically determine a player’s value – and, due to their low budget, look for undervalued players at the draft instead of the stars they couldn’t have bought anyway. Moneyball (2011) Their approach was extremely brave – and proved to be extremely successful. Instead of looking at throwing, fielding, hitting and r...
Source: The Medical Futurist - Category: Information Technology Authors: Tags: Forecast data sport sports baseball statcast MLB Source Type: blogs