Sports Analytics 101: The Pythagorean Theorem of Sports

In this video, I walk you through how the Pythagorean Theorem of sports (Baseball) works, and why it is such an important part of sports analytics. #DataScience #SportsAnalytics #PythagoreanTheorem Books: Mathletics: https://amzn.to/34k8vfv Trading Bases: https://amzn.to/349S6tD The Pythagorean theorem of baseball is a function of runs scored and runs scored against. With these two inputs we can very accurately approximate the win % of a baseball season. The equation for this is (runs scored)^2 / ((runs scored)^2 + (runs against)^2) If we can reliably project the expected runs scored and runs scored against for the next season, we can reliably extrapolate that to how many games they are expected to win. Wit this we can also evaluate how much of a positive or negative impact a new player will have on a team. We can predict the number of runs that a new player will create. With this formula, we are able to predict the number of wins that this accounts for. This is extremely important for teams when they are evaluating trades and valuing players. They can determine how much a player is worth based on the wins that they contribute. This equation can be related to other sports as well, although it is slightly less accurate. Because the number of points scored in football and basketball is higher than baseball, we have to adjust the exponent that we use in the equation #KenJee ⭕ 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://365datascience.pxf.io/P0jbBY 🌟 Interview Query - https://www.interviewquery.com/?ref=kenjee MORE DATA SCIENCE CONTENT HERE: 🐤My Twitter - https://twitter.com/K