Eck Sports Lab
Welcome
Welcome to the Eck Sports Lab!
At Eck Sports Lab, our mission is to research all things sports with a current focus on baseball. We study topics ranging from player evaluation metrics to comparing baseball players across eras. The common thread linking all of our projects is a dedication to high-quality and often innovative statistical and interdisciplinary research with a focus on an accessible and entertaining presentation of our ideas.
News
- 08/12/23 Daniel Eck presented “Comparing baseball players across eras via the novel Full House Model” at Saber Seminar 2023.
- 03/13/23 Our era-adjusted methodology and interdisciplinary collaboration was featured by the College of Liberal Arts and Sciences at University of Illinois Urbana-Champaign.
- 01/17/23 marks second iteration of the STAT 430 Baseball Analytics course at the University of Illinois Urbana-Champaign.
- 12/23/22 Our website housing era-adjusted statistics for nearly every player in baseball history is now live!
- The paper “Comparing baseball players across eras via the novel Full House Model” is now submitted for publication.
- The Eck Sports Lab is now collaborating with the Chicago Cubs on a joint undergraduate research mentorship program.
- 08/24/22 marks the inaugural session of the STAT 430 Baseball Analytics course at the University of Illinois Urbana-Champaign.
Current projects
Comparing baseball players across eras - This is an ongoing project devoted to the development of statistical tools which can era-adjust performance metrics. The impetus for this project was the initial discovery that the current consensus of baseball ranking methods were biased towards the performance of pre-integration players. You can read more about these origins here. Recently, we have made an advance towards the creation of era-adjusted statistics with the development of what we call the Full House Model. The Full House Model era-adjusts statistics through a principled balancing of how players performed “vs. their peers” and the quality of the talent pool of players’ contemporaries.
Here is a snapshot of our current results. Below is the top 10 list according to era-adjusted baseball reference wins above replacement (ebWAR) and era-adjusted fangraphs wins above replacment (efWAR):
| rank | name | ebWAR | name | efWAR |
|---|---|---|---|---|
| 1 | Barry Bonds | 154.80 | Barry Bonds | 152.69 |
| 2 | Willie Mays | 145.47 | Willie Mays | 138.04 |
| 3 | Roger Clemens | 141.78 | Roger Clemens | 131.18 |
| 4 | Hank Aaron | 129.65 | Hank Aaron | 125.00 |
| 5 | Babe Ruth | 122.81 | Babe Ruth | 119.16 |
| 6 | Alex Rodriguez | 121.01 | Alex Rodriguez | 116.66 |
| 7 | Greg Maddux | 111.58 | Greg Maddux | 115.29 |
| 8 | Albert Pujols | 111.03 | Mike Schmidt | 107.80 |
| 9 | Mike Schmidt | 110.43 | Rickey Henderson | 106.86 |
| 10 | Rickey Henderson | 107.79 | Nolan Ryan | 105.23 |
These stats are computed as if all players began their career in 1977; the list above includes both Babe Ruth’s batting and pitching WAR
Those interested in this project should check out our website.
Daniel Eck’s appearance on the Wharton Moneyball podcast (Eck’s appearance starts at 23:45, but the whole podcast is great) and his and Adrian Burgos Jr.’s appearances on the Effectively Wild podcast (Eck and Burgos appear at 53:34, but the whole podcast is great).
SEAM method for better batted-ball prediction - We develop the SEAM (synthetic estimated average matchup) method for describing batter versus pitcher matchups in baseball. The SEAM method provides confidence regions that reflect where baseballs that are put into play are expected to land. Our method is more accurate than similar methods constructed from individual batter spray charts or an individual pitcher’s spray chart allowed. We estimate that the implementation of SEAM can yield an additional 40 outs over conventional spray charts throughout the course of an MLB season. We have developed a web application that implements the SEAM method and provides visualizations.
Check out Julia Wapner’s presentation of the SEAM method at the 2022 SABR Analytics Conference:
People
Daniel J. Eck is a Statistics professor at the University of Illinois Urbana-Champaign. He is an active researcher in baseball analytics and has recently developed a topics course devoted to Baseball Analytics.
David Dalpiaz is a Statistics professor at the University of Illinois Urbana-Champaign. He is an active researcher in baseball analytics.
Adrian Burgos Jr. is a History professor at the University of Illinois Urbana-Champaign. He has written numerous books and articles and has taught numerous classes devoted to baseball history. Recently, Adrian served on Hall of Fame Committees which enshrined Bud Fowler, Gil Hodges, Jim Kaat, Minnie Minoso, Tony Oliva, and Buck O’Neil.
Christopher Kinson is a Statistics professor at the University of Illinois Urbana-Champaign. He is an active data science educator.
Shen Yan is a Statistics PhD student at the University of Illinois Urbana-Champaign. He has played a leading role in the development of the Full House Model.
Colin Alberts is an Applied Mathematics MS student at the University of Illinois Urbana-Champaign. He is working on optimal fielder placement.
Jamin Kim is a Statistics student at the University of Illinois Urbana-Champaign. He is working on a baseball game simulator with the Chicago Cubs.
Ryan To is a Computer Science student at the University of Illinois Urbana-Champaign. He is working on a baseball game simulator with the Chicago Cubs.
Henry Young is a Journalism student at the University of Illinois Urbana-Champaign. He is writing feature articles on players which incoporate era-adjusted statistics obtained via Full House Modeling.
Alumni
Jack C. Banks (2023) will be joining the New York Yankees as a Quantitative Analyst Associate. He worked on a baseball season simulator with the Chicago Cubs. Check out his website.
Michael Escobedo (2023) is a Statistics BS student at the University of Illinois Urbana-Champaign. He worked on a baseball season simulator with the Chicago Cubs.
Julia Wapner (2022) is currently working as an Analytics Fellow with the Baltimore Orioles. She helped develop the second version (current version) of the SEAM application.
Christian Chase Jr. (2022) worked as a Player Development Intern with the Chicago White Sox. He wrote his University of Florida honors thesis on "Predicting situation-specific OPS in MLB".
Charles Young (2020) is currently working as a Senior Front-End Developer with the Houston Astros. He helped develop the first version of the SEAM application. He created the Illini Analytics group at University of Illinois Urbana-Champaign. His collaborations with physicist and baseball expert Alan Nathan and the UIUC baseball team were made into a documentary.
Papers and resources
Challenging notalgia and performance metrics in baseball 
Comparing baseball players across eras via the novel Full House Model 
SEAM methodology for context-rich player matchup evaluations