How Much Did Cheating Help the Astros Win? (What the Numbers Say)

#DataScience #KenJee #SportsAnalytics #AstrosCheatingScandal The Code: https://github.com/PlayingNumbers/Astros_Analysis http://signstealingscandal.com/ https://gregstoll.com/~gregstoll/baseball/stats.html#V.1.8.0.1.0.0.2009.2018 https://www.playingnumbers.com/2020/02/did-cheating-really-help-the-astros-win/ In this video I walk through my analysis of the Astros Cheating scandal. From the data that Tony Adams collected, I look at the correlation between the number of trash can bangs and the number of runs scored. I also use a linear regression and a logistic regression to determine if trash can bangs have predictive power over runs and wins. Shockingly the correlation and linear regression suggested that there was very little relationship between bangs and runs scored. The logistic regression also suggested that bangs were not a predictor of wins. I was shocked by this, but I knew that I had to look deeper. After additional analysis, I found that the number of bangs in losses were significantly greater than the number in wins. If the Astros were mainly cheating when they were behind, this would likely not show in the models we built before. I also looked at the number of bangs in games when the Astros were down early. I found that there is a large spike in bangs when they are down in the first 3 innings. To see if this had a meaningful impact, I looked at their win % for games when they were behind by inning. I found that they greatly outperformed the average team when this was the case. #DataScience #KenJee #SportsAnalytics ⭕ Subscribe: https://www.youtube.com/c/kenjee1?sub_confirmation=1 🎙 Listen to My Podcast: https://www.youtube.com/c/KensNearestNeighborsPodcast 🕸 Check out My Website - https://kennethjee.com/ ✍️Sign up for My Newsletter - https://www.kennethjee.com/newsletter 📚 Books and Products I use - https://www.amazon.com/shop/kenjee (affiliate link) Partners & Affiliates 🌟 365 Data Science - Courses ( 57% Annual Discount): https://365data