Player & Team Analysis
Frameworks and case studies for evaluating players and teams: spotting real improvement, reading stat profiles, and separating signal from noise.
Evaluation is the hardest thing to do honestly, because the numbers that describe a player are the same ones that flatter him. This lane is a set of frameworks rather than verdicts: how to read a shot diet — the mix of rim, mid-range, and three-point attempts a player takes — and what it implies about efficiency; how to tell a real breakout from a good fortnight by asking whether the role grew and the efficiency survived the extra volume; and how the center's statistical profile was rewritten inside a decade. Two case studies put the frameworks to work on real data: one player's 1,652 tracked shots measured against the league's 25,000, and a test of whether the teams shooting the modern diet actually score more. The method is the point; the players are the worked examples.
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Does a Modern Shot Diet Actually Build a Better Offense?
Set each team's three-point share against its offensive rating and the correlation is a weak +0.21 — Denver took the fewest threes yet ranked fifth on offense.
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What 1,652 Shots Reveal About Luka Dončić's Shot Diet
Luka scores 1.15 points per shot (league: 1.09) while taking the shots analytics hates — 43% above-the-break threes and 18% mid-range. Why it still works.
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Reading a Shot Diet: What Shot Selection Tells You About a Player
Where a player shoots from says as much as how often he scores. How to read a shot diet — rim, mid-range, three, free throw — and what it reveals.
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Anatomy of a Breakout: A Statistical Framework for Spotting Real Improvement
Hot stretches fade; real leaps stick. A framework — usage, efficiency, role, and shot diet — for telling a breakout from a mirage.
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The Modern Center: How the Position's Stat Profile Changed in a Decade
The center that anchored 2014 offenses would look out of place today. We tracked how the position's statistical fingerprint changed, year by year.