Sports Analytics Weekly by kubeia.io - 21/2026
- Week 23
- Week 22
- Week 21
- Week 20
- Week 19
- Week 17
- Week 16
- Week 15
- Week 13
- Week 12
- Week 11
- Week 10
- Week 9
- Week 8
- Week 7
- Week 6
- Week 5
- Week 3
- Week 2
đź“ť Sports Analytics
Do radar plots need to die?
cannonstats.com - Scott Willis
Radar plots become an industry norm after being popularized by Ted Knutson formerly of StatsBomb. They are pretty to look at, and they can (and I believe do) give you a good quick look at a player.
They aren’t perfect by any means, no graphic is and this was pointed out in a post from PyMC-Labs called “Radar Plots Must Die.”
I use radars, and I plan on continuing to use them going forward and this made me want to directly address a few of the things brought up and what I do to address them or correct some things aren’t quite right.
PELE International Football Rankings âš˝
natesilver.net - Nate Silver
What happens when you blend 150+ years of soccer history and player market values into a brand-new model? You get PELE, our insanely detailed, predictive rating system for all 211 FIFA teams.
Does xG Predict Results Better Than EPV?
substack.com - Alex Marin Felices
The paper’s stated contribution is therefore to compare xG and EPV in both settings, asking whether shot-based information or possession-based information better predicts match outcomes when used before and after the game.
Football Radar Charts Are Misleading, A Better Way to Visualize Player Data
pymc-labs.com - Chris Fonnesbeck
Radar plots are everywhere in football (soccer) analytics. StatsBomb, The Athletic, FBref, and most analytics accounts on social media use them, and they arrive in my inbox through various football newsletters I subscribe to. They are eye-catching and compress a lot of metrics into one distinctive shape. But they are also, on reflection, a remarkably poor way to read a player: the polygon the reader perceives is driven more by arbitrary choices the analyst made than by the underlying numbers. The problems are not new, but this post summarizes them, surveys what the visualisations that do work have in common, and proposes a replacement built from those principles.
🤖 Machine Learning
Tabular ML is entering a new benchmark era
substack.com - Christoph Molnar
From static and narrow benchmarks to live, capability-driven evaluation