Ron Yurko
@Stat_Ron
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Assistant Teaching Professor, Director of Carnegie Mellon #SportsAnalytics Center https://t.co/bH22Ka8HwC @CMU_StatDS
Pittsburgh, PA
Joined March 2013
Excited to share that I'm working on a book: 'Statistical Methods in #SportsAnalytics'! This is the culmination of my education, research, and experience in teaching #statisticalthinking and modeling in #sportsanalytics! Thanks to Rob & @CRC_MathStats for the opportunity!
Delighted to have signed a contract with @Stat_Ron for an exciting new book on '#Statistical Methods in #SportsAnalytics' to be published by @CRC_MathStats in 2027! Watch this space for updates. https://t.co/0Hr8AiE86j
#DataScience #RStats @CarnegieMellon
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MNF Tonight: Watch the alternate broadcast on ESPN2! There will be an All-22 view! Dynamic pre-snap forecasting metrics! @FieldYates, @danorlovsky7 and @LukeKuechly breaking down the game! And @bburkeESPN as decision analyst to talk through 4th down and 2-point choices!
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@inpredict Have you seen this recent work. Idea is WP% numbers report are P(Win | game state) in that moment. Post-hoc look at the distribution of max WP% obtained by the loser, that's a just a different conditional distribution. https://t.co/jkeqKGoCU2
https://t.co/3gPOYenwy1
wsb.wharton.upenn.edu
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This is awesome! #BigDataBowl
Excited to share my submission for this year’s #BigDataBowl: “Ghostbusters: Back Off Man, I’m a Data Scientist!” Read the project here: https://t.co/ygU2npgdFl 👻
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Excited to share my submission for this year’s #BigDataBowl: “Ghostbusters: Back Off Man, I’m a Data Scientist!” Read the project here: https://t.co/ygU2npgdFl 👻
kaggle.com
Evaluating defender movement while the ball is in the air through hypothetical distributions of ghost defenders - By Lucca Ferraz
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Shedeur Sanders (161 plays) and Dillon Gabriel (217 plays), have nearly the exact same... Total EPA (-40.41 v -42.11) Pass EPA (-43.36 v -42.54) Success Rate (34.16% v 32.26%) Scramble Rate (5.63% v 5.14%) Sack Rate (8.41% v 8.13%)
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Wanted to show off a little of this app's functionality, check out the Pair Preference graphs for C2 and C3 league-wide: super strong preference for attacking the MOF and hole space vs C2, vs. attacking the deep out, deep seam and intermediate middle vs. C3
@Coach_Kay19 @CoachRyanLarsen If this seems limited, and you’re curious about how your favorite team plays its coverages or allocates its receivers, don’t worry! I’ve created an app that you can check out right now to explore these stats by team and coverage! You can access it here: https://t.co/x4azhmjA0G
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We’ve gotten OVERWHELMING excitement from both participants and NFL clubs on our new Analytics Competition. If you’re interested in sports data and analytics, and hope to work in the NFL and/or for major Sports companies, this is your chance! All entry and instructions below!
NEW: East-West Shrine Bowl x SumerSports Analytics Competition 📊🔢 An NFL data and analytics competition that lets anyone in the world have a chance to showcase their models and present to NFL decision makers at the East-West Shrine Bowl. Show how your ideas can help evaluate
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STRAIN is back - but for #NFL pass coverage! Check out this #BigDataBowl submission by a team of @CMU_StatDS MADS students: Avery Wang, Alex Hill, Pramit Vyas, & Tyler Quinn https://t.co/iQ7Uf4GEAp - they introduce the Receiver-Ball Preference Index (RPI) #sportsanalytics #CMSAC
kaggle.com
Comparing conservative tacklers to all-in ball hawks, and everything in between.
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That moment when the Annals of Applied Statistics acceptance email arrives
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Check out @CMU_StatDS MADS ( https://t.co/ex6WSfWow4) student Ani's #BigDataBowl submission introducing Separation Elimination Against the Line-to-gain (SEAL)! https://t.co/U2ZxkMd1Gm
#NFL #sportsanalytics
kaggle.com
Quantifying how defenders eliminate separation to prevent first-down conversions
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Check out the #BigDataBowl submission by CMU freshman(!) Archith Sharma and sophomore(!) Theresa Pham on measuring #NFL defender commitment while the ball is in the air using geometry! https://t.co/G72AFF5Dcs
#sportsanalytics #CMSAC
kaggle.com
Measuring a defender's commitment to the ball when it is in the air and its impact on play outcomes.
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Check out the #BigDataBowl submission by CMU sophomore(!) and @TartanFB equipment manager Tate Helms! He introduces new metrics to consider based on observable quantities from the #NFL player-tracking data #sportsanalytics
kaggle.com
Playing with Distance, Speed, and Time
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This is pretty cool. Some @TartanFB coaches gave some insight to the Big Data Bowl crews at Carnegie Mellon. Interesting analysis.
Really excited to share my #BigDataBowl Submission for 2026! This is Window Shopping: a study on how defenses protect and close down field spaces, and how offenses open those spaces up. I’m really proud of this year’s work, and I’m going to be breaking it down in this thread!
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@Coach_Kay19 To answer these questions, I talked with @CoachRyanLarsen about how offenses divide the field into areas of attack, which I then used to divide the field and determine which spaces receivers were occupying. He sent me a drawing, which I converted into my field divisions.
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Check out @Abhiv05's #BigDataBowl submission! https://t.co/bwnN79seN1 Abhi did an awesome job on this, seamlessly blending his football knowledge with his StatsML skills, building this analysis based on conversations with our fantastic @TartanFB coaches! #NFL #sportsanalytics
Really excited to share my #BigDataBowl Submission for 2026! This is Window Shopping: a study on how defenses protect and close down field spaces, and how offenses open those spaces up. I’m really proud of this year’s work, and I’m going to be breaking it down in this thread!
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Will be tweeting about each of these throughout the day - in separate tweets because I don't understand how threads work here any more
We have 6(!) #CMSAC #NFL #BigDataBowl submissions: + https://t.co/iQ7Uf4G6KR + https://t.co/G72AFF5Dcs + https://t.co/Rk728Aap8S + https://t.co/U2ZxkMd1Gm + https://t.co/bwnN79seN1 + https://t.co/ZuBzSncuNm I'll share more about each tomorrow, but congrats to all that entered!
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@Coach_Kay19 @CoachRyanLarsen Many thanks to @CoachRyanLarsen , @CoachGibboney , @CoachAndyHelms , and @Coach_Kay19 for all the scheme discussions in their offices and at practice this semester. I learned so much from them and it was invaluable in developing this project.
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@Coach_Kay19 @CoachRyanLarsen If you’d like to read my full writeup, you can check it out here!
kaggle.com
An investigation into how defenses protect and close down zones on the field, and how offenses attack those spaces with their receivers.
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@Coach_Kay19 @CoachRyanLarsen In particular, I think using separation change percent with more specific knowledge of how defenses run certain calls (e.g., spinning coverages so angles are different) and using pair percentage with more explicit play call data could both be excellent applications for this work.
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@Coach_Kay19 @CoachRyanLarsen Overall, I think there were some really cool conclusions from this work! The stats I made aligned with a lot of prior understanding of scheme, and I think there are some really cool applications for this work going forward.
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