A Model to Find the Most Average NBA Player
https://youtu.be/0I2T0R91G38
> Who is the most statistically average player in the NBA?
> Not the 250th-best player. Not the most mediocre player. I wanted the player who sits closest to the actual center of the NBA — physically, statistically, stylistically, and everything in between.
> So naturally, I built an unnecessarily complicated system called B.A.S.I.C. — the Basketball Averageness Similarity Index Calculation.
> We start with a horribly broken definition of “average,” then progressively make it worse by adding:
- Player size and age
- Playing time and role
- Per-possession production
- Efficiency
- Shot profile and play style
- Offensive and defensive impact
- Correlation adjustments
- Mean vs. median
- Thousands of randomized definitions of “average”
> Until eventually, one player refuses to stop being normal.
> And because apparently that wasn’t enough, I also used the results to construct the literally average NBA player: John Basketball.
> All of this work to scientifically discover the role player.
> Fantastic.
Fun modeling exercise. @SimpleStacker and I feel your pain.
https://stacker.news/items/1594803
npub1t4…w4jj5
2026-10-13 19:12:58 UTC
Author Public Key
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wss://relay.damus.ioPublished at
2026-10-13 19:12:58 UTCEvent JSON
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"content": "A Model to Find the Most Average NBA Player\nhttps://youtu.be/0I2T0R91G38\n\n\u003e Who is the most statistically average player in the NBA?\n\n\u003e Not the 250th-best player. Not the most mediocre player. I wanted the player who sits closest to the actual center of the NBA — physically, statistically, stylistically, and everything in between.\n\n\u003e So naturally, I built an unnecessarily complicated system called B.A.S.I.C. — the Basketball Averageness Similarity Index Calculation.\n\n\u003e We start with a horribly broken definition of “average,” then progressively make it worse by adding:\n- Player size and age\n- Playing time and role\n- Per-possession production\n- Efficiency\n- Shot profile and play style\n- Offensive and defensive impact\n- Correlation adjustments\n- Mean vs. median\n- Thousands of randomized definitions of “average”\n\n\u003e Until eventually, one player refuses to stop being normal.\n\n\u003e And because apparently that wasn’t enough, I also used the results to construct the literally average NBA player: John Basketball.\n\n\u003e All of this work to scientifically discover the role player.\n\n\u003e Fantastic.\n\nFun modeling exercise. @SimpleStacker and I feel your pain.\n\nhttps://stacker.news/items/1594803",
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