@JDPipping
🇺🇸Account based in
About this account
- Account based in
- United States
- Connected via
- United States App Store
Account-level information from X, not a live location or the device used for a specific post.
don’t forget to give.
Joined August 2022
- Tweets11
- Following99
- Followers57
- Likes21.4K
Jonathan Pipping retweeted
You (analysts) don't have to make the choice––the coach does. When the estimated edge is small relative to its uncertainty—and knowing that models cannot capture all relevant information—a coach can reasonably choose the option your model ranks lower.
Jonathan Pipping retweeted
Biannual reminder: when people say "probabilities" they often should be saying "estimated probabilities". Estimates can be (often are) far from rock solid: complex feature space & sample size is smaller than you'd think --> we're uncertain about the estimates we've produced
Jonathan Pipping retweeted
Great paper on this subject by @RyanBrill_ & @adiwyner arxiv.org/abs/2311.03490 #analyticshavesomehumility
YES!
This is a great take on the subject!
We talked about this on the show a few weeks back.
You can't just treat it like poker or blackjack, cos you don't necessarily get the time for the math to work in your favor.
What's that line, the market can remain irrational longer than you can remain solvent? Same idea.
You want the information; you don't want to go with the edge lean every single time just cos it says 51%.
Jonathan Pipping retweeted
Steelers 26, Buccaneers 19. Oct. 18, 2026.
Tampa Bay (41.5%) reached 91.0% win probability, up 16–3 with 0:00 left in Q3.
Under our benchmark, a collapse this extreme occurs in 9.93% of games. For teams starting at 41.5%, 7.03% of losses are this extreme.
WP: @ESPN
ALT A line chart shows Tampa Bay Buccaneers win probability throughout the game against Pittsburgh Steelers on Oct. 18, 2026. Final score: Pittsburgh Steelers 26, Tampa Bay Buccaneers 19. The highlighted peak is 91.0%, up 16–3 with 0:00 remaining in Q3. The first reported win probability was 41.5%. Source: ESPN.
Jonathan Pipping retweeted
Blown leads happen more often than you think.
When a team loses a game it looked certain to win, how surprised should we really be?
A @WhartonSABI project.
Excited to share my first #WSABI Research Note with Professor @adiwyner, where we explore why "blown leads" are far more common than they seem! Full probability paper coming 🔜
How rare is it for an @NFL team to squander a seemingly comfortable lead?
@Wharton Ph.D. student @JDPipping & @adiwyner examine win probability models & demonstrate that these “collapses” are actually far more common than they seem.
Read here → whr.tn/3UtuNH8
Jonathan Pipping retweeted
Incredibly hyped and grateful!! Thankful for awesome teammates @ColeJacobson32 @JDPipping & for @StatsbyLopez @DataWithBliss & NFL for hosting!! A remarkable & fun competition, a real bright spot & cornerstone of sports analytics! Very impressed with this year’s entries.
Congratulations to the Finalists, Semi-Finalists, and Honorable Mention finishers in the 2025 Big Data Bowl #BigDataBowl
Jonathan Pipping retweeted
Excited to share this year's #BigDataBowl entry w/ @RyanBrill_ & @JDPipping. We built a model using safeties' pre-snap movements to predict coverages, & we identified defenses' key tells, plus which teams disguise the best. S/o @StatsbyLopez for organizing
bit.ly/4gUBs6E