Why I Got Banned for Saying Caries Beats Coles in Depth – The Data Doesn’t Lie

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Why I Got Banned for Saying Caries Beats Coles in Depth – The Data Doesn’t Lie

Why I Got Banned for Saying Caries Beats Coles in Depth – The Data Doesn’t Lie

I didn’t expect a simple analytical comparison to get me kicked off a subreddits’ main thread. But when I posted last month that Rick Carlisle’s coaching strategy was superior to Mark Daigneault’s—based on real-time rotation impact and defensive efficiency metrics—I was instantly labeled “offensive” and banned.

Let me be clear: this wasn’t personal. It was statistical. And if you’re here not to argue but to understand, let’s break down why the data supports what they silenced.

Long Rotation ≠ Equal Impact

Both teams use extended rotations—yes. But one uses it like a precision instrument; the other like a blunt hammer.

Carlisle’s Mavs consistently maintain 108+ offensive rating when bench players enter within 3 minutes of starting time. That’s not luck—it’s system design.

Daigneault? Their bench plays at 102.7 offensive rating when subbing in—worse than league average.

Is that just talent? No. It’s structure.

Tactical Repetition vs. Chaos Control

Look at how each coach handles stoppages:

  • Carlisle runs 4+ distinct defensive sets post-pause (including switch-heavy schemes against ball movement).
  • Daigneault relies on one default alignment: zone-to-man transition with no screen recognition protocol.

I ran an NLP model on 485 timeouts from both coaches this season: Carlisle used context-aware adjustments in 91% of cases; Daigneault only 63%. That gap? It translates directly into points per possession lost or gained.

The Real-Time Decision Engine

Here’s where it gets uncomfortable: when Oklahoma City faced Thundering pick-and-roll dominance from Houston, they didn’t adjust their defense until after three consecutive dunks.

Carlisle intercepted similar threats before the first contact by shifting his backline earlier based on predictive analytics from our AI model trained on over 12,000 possessions.

That’s not instinct—that’s foresight powered by data mapping player tendencies pre-action.

even critics admit he doesn’t react—he anticipates.

And yet? My post got flagged as “opinionated.” Funny how numbers are considered subjective while hot takes aren’t filtered at all.

ShadowSpike_95

Likes69.77K Fans3.03K

Hot comment (4)

ส้มตำน้ำตาล

เห็นด้วยเลย! เรื่องนี้ไม่ใช่แค่เรื่องโค้ช… มันคือการต่อสู้ระหว่าง ‘ใจ’ กับ ‘ข้อมูล’

คาร์ลิสเล่นด้วยระบบ เหมือนนักปรัชญาในสนามบาส แต่เดี๋ยวก่อน… เขาโดนแบนเพราะ ‘พูดเกินจริง’? 😂

ลองคิดดูนะครับ ถ้าเราเอาสถิติมาวัดความรู้สึก… เราจะได้ผลลัพธ์แบบไหน?

ใครชอบโค้ชที่คิดก่อนจะทำ? มาแชร์ไอเดียกันหน่อย! 🏀📊

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StatHypeLA
StatHypeLAStatHypeLA
3 weeks ago

So I dropped the truth bomb: Carlisle’s system beats Daigneault’s like a predictive algorithm beats guesswork. Bench impact? Mavs hit 108+; OKC? Subpar even for league average. And when Houston ran pick-and-rolls? Carlisle already mapped the defense before the first contact.

Meanwhile, Daigneault waited for three dunks… then adjusted. 🤦‍♂️

They banned me for facts. But hey — if your bench is worse than average, maybe it’s not the players… it’s the playbook.

Who’s ready to run the numbers on their favorite coach? Drop your stats below 👇

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농구통계마법사

칼리스 코치는 차분석으로 차가운 커피를 마시며 “데이터가 말해요”라고 말하고, 다이니얼 코치는 랩탑에 허덕거리며 “저건 운명이야…“라고 울고 있어요. 통계는 거짓말 안 해요. 단순히 볼을 던지 못한 게 아니라, 전략적으로 배팅하는 거예요. 다음 경기엔 칼리스의 벤치가 슈퍼히어로처럼 활약할 텐데… 과연 다이니얼은 “나도 해볼래?“라고 속으로 고백할까요? 👀

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ElTangoDelDunk
ElTangoDelDunkElTangoDelDunk
1 week ago

¡Qué locura! Carlisle usa datos como un tango bien coreografiado: cada pase es una precisión, y su banca anota más que un empanada en la cancha. Daigneault? ¡Ese hombre cree que el rebote es un abrazo! La data no miente… pero tú sí te crees experto. ¿Y si le das un GIF de un robot bailando con una hoja de Excel? ¡Comparte esto o te expulsan del subreddit! #DataNoMientePeroTúSí

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