Eck Lab

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Welcome

Welcome to the Eck Lab!

At Eck Lab, our mission is to research all things baseball. We study topics ranging from player evaluation metrics to comparing 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

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 replacment (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

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 spracy 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 - Daniel 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 at the University of Illinois (see the Syllabus here).

David Dalpiaz - David is a Statistics professor at the University of Illinois Urbana-Champaign. He is an active researcher in baseball analytics.

Adrian Burgos Jr. - Adrian 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 - Christopher is a Statistics professor at the University of Illinois Urbana-Champaign. He is an active data science educator.

Shen Yan - Shen is a Statistics PhD student at the University of Illinois Urbana-Champaign.


Colin Alberts - Colin is an Applied Mathematics MS student at the University of Illinois Urbana-Champaign.


Jack C. Banks - Jack is a Statistics BS student at the University of Illinois Urbana-Champaign. Check out his website.


Michael Escobedo - Michael is a Statistics BS student at the University of Illinois Urbana-Champaign.


Alumni

Julia Wapner (2022) - Julia is currently working as an Analytics Fellow with the Baltimore Orioles.


Christian Chase Jr. (2022) - Christian is currently working as a Baseball Operations Intern at MLB and UF Baseball Data Intern. Check out his baseball website.

Charles Young (2020) - Charles is currently working as a Quantitative Developer with the Houston Astros.


Papers and resources


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