Sports Stats Explained
At TheDataJocks, we love explaining how and why sports stats work the way they do. Why are they defined the way they are? Are they good at what they do? How should they best be used and applied? Studying how we come up with sports stats improves both our mathematical knowledge as well as our understanding of the game. Below, find links to all our articles explaining how different statistics work in sports.
Why do we use WHIP to measure how good a pitcher is? We look at this stat and whether or not it is valuable.
We look at RPI in College Sports. What is it, what problem it tried to solve, how it was calculated, and why it isn’t used anymore
Strength of Record combines strength of schedule and your record to estimate team quality. Lots of metrics do this, does strength of record succeed?
Why is strength of schedule so difficult to measure in sports? And why is it so important to study?
Expected Goals is the premier soccer analytics tool. We look at how it uses logistic regression to analyze player quality
In baseball, players performance can fluctuate due to random chance. BABIP, in a fascinating way, helps us understand which players have been lucky or unlucky
ELO ratings show up everywhere from online gaming to chess to 538’s NBA (carmELO) and NFL rating systems. But how does ELO work?
Passer rating and QBR both try to rate quarterback performance. But they are distinctly different. Which is better?
Real plus minus puts a mathematical twist on a traditional box score stat. What does it change from regular plus/minus and why?
In the NBA, PER is a great stat to estimate the total impact of a player’s on-court contributions. We look at how it is computed and, more importantly, why it is computed that way.