
Patrick A. Peterson, PhD
1.1K posts

Patrick A. Peterson, PhD
@ppeterson_
The Real Patrick Peterson. Numbers guy. @RFootball #CHOP 🪓
Katılım Mart 2018
2.4K Takip Edilen608 Takipçiler

It has absolutely been questioned, the original data comes from Counsilman’s paper from the 80’s where he looked at his swimmers subjective feelings of speed power etc in events and then their training logs prior to it was and always had been conjecture. No control groups nothing. There are actually more recent detraining studies in soccer and rugby athletes that I’ve come across where they go 2-3 weeks with nothing and no significant declines in MSS some showing improvements.
People have taken this chart as written law or truth when in reality Counsilman himself proposed it as a framework, basically a principle of his training plans for a non-locomotor sport. Way overblown!
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Let’s do it 🫡
Thanks to @DropbackHQ for affording us this opportunity to grow

Dropback@DropbackHQ
Staff from @RFootball have been accepted into the Spring 2026 cohort of Dropback's Front Office Academy 💥 Learn more 👇
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Hey man I really love your content, been reading for some time now. Excited to see what you guys do at DropBack...
I am pretty sure the model you've created here is actually a piecewise (segmented) regression. Stepwise regression is for feature selection (i.e. adding or removing covariates based on AIC). I definitely agree with the theory here but the write up might be a little confusing since the results are a univariate model and stepwise regression is used for big models (I use it a lot with recruiting data).
Some more interesting stuff you can find with piecewise (or segmented as its commonly called) is what type of anthropometric measures actually matter and at what levels of other variables (i.e. arm length doesn't matter as much at 6'5"+ because your wingspan with your shoulder/torso is already so wide).
Heres another example on piecewise (segmented) regression using NFL data:
journals.lww.com/nsca-jscr/full…
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One way to think about how to interpret speeed/measurables outside of tape is with a stepwise regression. Give credit based on certain thresholds, and specifically penalize players who don't make the thresholds.
Player goes from 4.5 to 4.7? -35 percentage points
From 4.4 to 4.3? +5 percentage points


parker fleming@statsowar
Jotted down some words about interpreting athleticism in player evaluation. Written in the context of the combine, but applicable to college recruiting/portal certainly.
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Patrick A. Peterson, PhD retweetledi

“Babe - If all you ever do, is all you ever done. Then all you ever get, is all you ever got.” @TomBrady 😉
@TheHall | @Edelman11
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Patrick A. Peterson, PhD retweetledi
Patrick A. Peterson, PhD retweetledi
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Rookie CBs ranked by passer rating allowed so far in preseason:
#Chargers Eric Rogers (0.0)
#Bears Jeremiah Walker (39.6)
#Chargers Nikko Reed (39.8)
#Texans Jaylon Smith (46.3)
#Ravens Marquise Robinson (50.3)
#Vikings Zemaiah Vaughn (51.0)
#Titans Marcus Harris (57.1)
#Ravens Keyon Martin (66.0)
#Patriots Kobee Minor (69.7)
#Bucs Jacob Parrish (70.5)
…
#Broncos Jahdae Barron (79.2)
#Saints Quincy Riley (91.7)
#Chiefs Nohl Williams (100.0)
#Cardinals Denzel Burke (110.0)

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Patrick A. Peterson, PhD retweetledi

GPT-5 just casually did new mathematics.
Sebastien Bubeck gave it an open problem from convex optimization, something humans had only partially solved. GPT-5-Pro sat down, reasoned for 17 minutes, and produced a correct proof improving the known bound from 1/L all the way to 1.5/L.
This wasn’t in the paper. It wasn’t online. It wasn’t memorized. It was new math. Verified by Bubeck himself.
Humans later closed the gap at 1.75/L, but GPT-5 independently advanced the frontier.
A machine just contributed original research-level mathematics.
If you’re not completely stunned by this, you’re not paying attention.
We’ve officially entered the era where AI isn’t just learning math, it’s creating it. @sama @OpenAI @kevinweil @gdb @markchen90

Sebastien Bubeck@SebastienBubeck
Claim: gpt-5-pro can prove new interesting mathematics. Proof: I took a convex optimization paper with a clean open problem in it and asked gpt-5-pro to work on it. It proved a better bound than what is in the paper, and I checked the proof it's correct. Details below.
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Patrick A. Peterson, PhD retweetledi
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Patrick A. Peterson, PhD retweetledi
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Congratulations to DT Sheffield @Dtsheffield3 for being named to the Biletnikoff Award Preseason Watch List! The Biletnikoff Award recognizes the college football season's outstanding FBS receiver at any position. @RFootball @RUAthletics #OutstandingReceiver #NCFAA

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