Little basketball analytics rant. I’ve been seeing more and more people on my timeline use points-per-possession (“PPP”) when talking about actions (and even shooting?). Maybe my timeline has just gotten more college basketball-heavy, but PPP has quietly become a catch-all stat, and it’s getting stretched way past what it measures. PPP is a team efficiency number. It’s great for game- or season-long efficiency, and it’s usually what you’re seeing reported as offensive/defensive rating. When we’re measuring action-level events (picks, drives, isolations, etc.), we want points-per-chance (“PPC”). A chance splits possessions into distinct scoring opportunities, broken up by offensive rebounds and dead balls. Say you run a pindown and the pass gets deflected out of bounds. From the side-out, you run something else and score two. The pindown produced zero points, but PPP credits it with two because you scored on the same possession. PPC gives it zero. If you want to be more precise, you can attribute putback points to the chance that created the miss. Then there’s the concept of direct chances (and true points/shot for shooting!), but this post is already long enough.

Posted and turned on football. Anyways, closing thoughts: Location is a pretty blunt proxy. My data doesn’t capture most of what makes a shot "good" or "bad." Rhythm, balance, contest strength, and who’s shooting matter more than the spot. And not every three is a good three either! There’s a place for the midrange. Some guys are really good at it. Some defenses take away the rim/three and you need a counter. A good shot for one guy is a bad shot for another. That’s where coaching comes in. Know your personnel, get buy-in, and build the right habits in practice. But all things considered, the midrange usually isn’t an efficient look. Especially in college, where there’s no defensive three seconds and most guys just aren’t good enough shot creators to live there. Shot diets built around the rim and catch-and-shoot threes (paint-kicks, perimeter-swings, etc) win long term. (I paid Elon $4 to write a longer post, smh)

group chat reignited two age-old debates: a) can one all-nba player make the worst-rated kenpom team a national title contender? b) who is the worst nba player who would make a 16-seed even money to reach the final four?

Duke has their 7’2” 250 17yo running PnRs with their 6’11” 250 center It’s beautiful. Give me more.

Over 200,000 D-I vs. D-I games in the 64-team era have produced 3,748 different final scores. Only 15 were new ("a scorigami") in 2025–26, and Georgia and Ohio State had two each. Most were 40-point blowouts, and there were none after Dec. 20. 👇👇👇

Willing to make these for some different teams. If you want to see one for yours, comment below 👇

With Cam Boozer and Isaiah Evans gone, here's where Duke's returners and transfers shot from last season. Dame Sarr made 34 corner 3s, tied for the most of any high-major player, and John Blackwell made 32. Caleb Foster took just 8 midrange shots.

No high-major returner's shot share jumped more in crunch time last season than Jeremy Fears Jr.'s. He went from taking about 1 in 5 of Michigan State's shots while on-floor to nearly half when games got tight. 👇👇

Thank you, Tom, for my love of sports and numbers. Thank you for every media guide I took and every roster I tried to memorize. I will forever cherish the beach trips, the stops at Sheffields, the weather updates, the basketball practices, and all of the years in between ❤️❤️❤️

After two years, gtUtils is getting an update. v1.0 ships with 27 new functions and 10 new themes, all of which sit nicely atop existing {gt} workflows. Per-cell coloring, facet layouts, percentile bars, cut lines, legends, export helpers, + more! gtutils.aweatherman.com