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2026 SMT Data Challenge Information
Finalist Showcase Weekend: October 30-November 3, 2026

2026 Finalists and Honorable Mentions

PROJECT TOPIC: On the Big Screen!

At its core, baseball is entertainment. The technological advancements in baseball have always strived to increase fan understanding of the game. SMT amplifies fan engagement with real-time data visualization tools, changing the game by how we tell stories for all audiences. In 2026, we want your help in telling stories better through a metric, visualization, or interactive fan experience that could be displayed on a Minor League Baseball scoreboard.​​​

| Finalists

Finalist teams are invited to a showcase weekend at SMT headquarters in Durham, NC to present to a panel of judges (October 30-November 3).​​

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TEAM 10: Andrew Zaletski (UC San Diego)

Through the Batter's Eye: An Interactive Fan Experience on Pitch Identification and Swing Decision

This project delivers an interactive fan contest built for in-stadium, mid-inning play: a real-time pitch guessing game in which the fan watches a real ball-tracking trajectory animate from the mound to the plate, then identifies the pitch type and whether to swing or take. Correct reads on in-zone pitches advance the at-bat, while bad reads, chases, and called strikes count against you, replicating the same pressures a major league hitter faces in the box. Behind the game, a Gaussian Mixture Model trained on velocity, horizontal break, and induced vertical break assigns pitch-type labels to anonymous ball-tracking data, giving each pitcher a simulated arsenal grounded in their real movement patterns.

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TEAM 143: Shravan Agnihotri (Queen's University), Shun Chen (University of Western Ontario), Elliot Sones (Toronto Metropolitan University)

Shift Happens

Shift Happens is a fan-facing jumbotron game, powered by SportsMEDIA Technology (SMT) minor league player-tracking data. The objective of the game is to shift the defensive positioning of your players to improve the chances they catch the ball and make the out. A few times each ballgame, between innings, the jumbotron calls on fans to scan a QR code and step in as the defensive manager for a historical play. Fans are handed real game context before making their call, seeing the batter's handedness and spray chart, along with how fast their outfielders are. With that information, fans are trusted to make the right decision themselves, given thirty seconds to decide how to shift around their players for the upcoming play. When the timer runs out, the jumbotron reveals what actually happened alongside every fan's call, showing exactly how their decision compares to the real outcome. Fans earn points based on how much their positioning helped or hurt the play, factoring in how quickly they locked in their answer. Climb the leaderboard, think critically and decide under pressure, racing to outscore the rest of the stadium and be named Manager of the Night.

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TEAM 204: Ilan Blumenthal (Binghamton University), Benjy Baronofsky, Jonathan Paris (Washington University in St Louis)

It's GO TIME!: Quantifying Tag-Up Reaction Time to Increase Fan Engagement

The outcome of a baseball game is often decided by inches. When a runner on third base tags up, beating the throw home requires more than raw speed, it requires a split-second reaction. In this paper, we uncover the hidden race before the sprint, translating a runner’s reaction time into a dynamic new metric: GO TIME . Using minor league player tracking data, we analyzed 109 competitive tag-up plays to measure the exact delay between the outfielder's catch and the runner's break for home. To make it even more engaging, we developed stadium scoreboard graphics to display a player’s GO TIME and how his GO TIME ranks. The scoreboard graphic also puts players’ times into perspective, using comparisons such as the time it takes to blink, or how fast a fastball reaches the plate. We also created an interactive fan experience where fans can test their own GO TIMEs against other fans and baseball's best. GO TIME leverages advanced player tracking along with an immersive fan experience to offer a deeper insight into baserunning efficiency while also boosting fan engagement.

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  • Tea

| Honorable Mentions

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TEAM 88: Ethan Cappelleri, Sam Cowan, Evan Kurtz, Tejas Rama (Boston University)

"Wanna See Me Do it Again?": Dynamic Catch Probability Visualization through ManimGL 

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TEAM 102: Pierre Aucoin (University of Waterloo)

Is It Deep Enough? An Analysis into Sac Fly Distance

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TEAM 107: Theodore J. DeFuria (Northeastern University)

Fair or Foul

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TEAM 111: Aiman Fariz Zaqwan Bin Akmal Hizam (University of Tulsa)

Crowd Call

 

TEAM 144: Amin Nabavi (Carleton University)

Tunnel Vision: Putting Pitch Deception On the Big Screen

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TEAM 158: Reuben Feingold (Colgate University)

Freeze Frame: A "BEAT THE FREEZE" VISUAL 

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TEAM 166: Sonya Lasser (Duke University)

Triangle Tribulations

 

TEAM 227: Shirin Alapati, Jake Crumley, Ethan Nepo (San Jose State University)

Game of Inches: Visualizing the Impact of Outfield Positioning on Catch Probability

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TEAM 308: Evan Delcamp (University of Michigan), Aaron Siminou (Duke University)

Bringing a Gun to a Swordfight:  The Deceptive Art of the Pitchers’ Duel

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| General Information


The SMT Data Challenge is an advanced data competition where students analyze real-world, baseball tracking data. Projects are open-ended, emphasizing process, relevance, creativity and communication rather than purely quantitative analysis. The Data Challenge has become a top recruiting ground for MLB teams—more than 25% of past participants have been hired by professional teams or sports companies.


IF YOU WANT TO STAND OUT AS A JOB CANDIDATE, THIS IS WHERE TO START!

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| Eligibility

 

  • The SMT Data Challenge is open to STUDENTS ONLY.

  • Must be 18 years or older and enrolled for both Spring and Fall 2026 semesters 

  • Students may participate individually or in teams (max: 4 students). There is also an option for individuals looking for team members. ​​​​​​​​​

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| Judging

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Judges from academia, industry, journalism, and sports will evaluate submissions based on creativity, relevance, methodology, storytelling and communication to technical and non-technical audiences.

| Submission Requirements

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  • Abstract 

  • Narrative Paper (max: 2000 words)

  • Analysis Code

​| Tutorials​

 

Tutorials will cover the following topics:​​

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  • Math Review

  • Feature Engineering

  • Data Visualization

  • Supervised Regression

  • Supervised Classification

  • Paper Writing

  • Sports Hiring Process

| Finalist Showcase

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Finalist teams will be invited to a showcase weekend at SMT headquarters in Durham, NC to present to a panel of judges. (Mid-Late Nov, date TBD)

| Key Dates (2027)

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March 11: Project Topic Announced

April 28: Registration Deadline

April 30: NDA Deadline

May 3: Earliest date Data might be available

July 26:  Submission Deadline

Oct 4: Finalists Announced

Mid-Nov: Finalist Presentations

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