Ever yelled at the TV, convinced you could make a better call than the coach? Ever argued with friends about which player is really the most valuable?
Now’s your chance to prove it. We’re calling all data enthusiasts, sports fanatics, and creative problem-solvers to compete in a challenge that puts you in the game. Use real-world data to uncover insights that could redefine team strategy and player evaluation.
About the Competition
Each Spring semester, the Texas A&M Institute of Data Science (TAMIDS) hosts a seven-week-long data science competition open to all Texas A&M undergraduate and graduate students. The TAMIDS’s Student Data Science Competitions website has more information about past competitions, their themes, and winners.
The 2026 Sports Data Challenge is an open-ended data science competition where teams of 1-5 students identify a goal, conduct an analysis, develop a final report, and present their findings for a chance to win prize money. The competition is focused on the intersection of AI, athletics, Kinesiology & Sport Management, and data science.
Ever wonder how teams find their winning edge? It’s not just grit—it’s data. Sports analytics is where the passion of the game meets the power of numbers. We use data to answer the big questions: Who is the most undervalued player? What play call gives the best chance to win? How can we predict the next superstar? In modern sports, the biggest victories often start with a line of code.
The Registration Deadline is Sunday, February 22, 2026, at 11:59 PM CST
Join the TAMIDS Discord
Check out past competitions
Read the competition rules
Competition Canvas Site*
* The competition’s Canvas Site will be available after the Kick-off Session, and only to competitions, starting on February 26, 2025.
Sport x Data Science
The inclusion of AI and data science in sport represents a fundamental shift from simple scorekeeping to sophisticated, predictive strategy. For decades, sports relied on descriptive metrics like batting averages and points per game to summarize past performance. Data science revolutionizes this by applying machine learning, statistical modeling, and advanced algorithms to vast, complex datasets (e.g., player-tracking computer vision, biometric data from wearables, digital twins of players and twins). This collaboration allows teams to move beyond merely recording what happened and begin to understand why it happened, enabling them to uncover hidden patterns, quantify player impact more accurately, improve player health and performance, and ultimately replace intuition with evidence-based insights to gain a competitive edge.
In practice, this intersection transforms every level of a sports organization. On the field, analytics drives in-game decisions, such as optimizing defensive shifts in baseball, determining the most effective play calls in football, and creating ideal player lineups in basketball. In the front office, data-driven models guide scouting, contract negotiations, and draft strategy, helping teams identify undervalued talent in a “Moneyball” fashion. Furthermore, data is now crucial for player development and health, with teams analyzing workload data to prevent injuries and optimize training regimens. This fusion has created a new standard of competition where the most successful teams are often the ones who best harness the power of their data.
Competition Schedule
FEBRUARY 22 — Registration Deadline
All competitors must register using the competition’s REGISTRATION FORM by Sunday, February 22, 2026, 11:59 pm CST; otherwise, they will not be included in the competition. If you are looking for teammates, join TAMIDS’s Discord Server and check out the “team-member-hunt” channel.
FEBRUARY 26 — Kick-Off Session
The competition’s kick-off will be held on Thursday, February 26, from 6:00–9:00 pm, in person in the Interdisciplinary Life Sciences Building (ILSB) auditorium, with remote participation via Zoom (the event link will be available via the registration confirmation). Drinks and snacks will be provided for in-person attendees.
MARCH 5 — Workshop and Q&A
The organizers will host an online workshop and Q&A session on Thursday, March 5, from 6:00–9:00 pm, to support participants in developing essential skills and understanding for the competition. This interactive session will cover practical techniques for tackling data science challenges and background insights into sports. Participants will also benefit from personalized guidance during the open Q&A session, where they can seek advice on their specific projects or clarify competition details. Designed to enhance your learning experience and boost your confidence, this workshop is a valuable opportunity to refine your approach and gain insights that can set your team apart. The Zoom link is accessible only to registered email addresses.
MARCH 18 — The Midpoint Showcase
The special midpoint event will be held on Wednesday, March 18, from 6:00–8:00 pm. The event will include a special activity, and we will announce the winners of the Midpoint Summary – “Best Visualization” Prizes.
APRIL 2 — Team Report Due
Teams will submit a single report through the competition’s Canvas site by Thursday, April 2, 2026 (11:59 pm). Multiple updates are allowed before the deadline, but no late submissions will be accepted. After the submission period closes, judges will review all entries and select participants to advance to the final round of the competition.
APRIL 9 — Finalists Announced
Finalist teams will be notified through email by Thursday, April 9, 2026. and listed on the competition’s Canvas site and Discord server. These teams have one week to prepare a presentation for the Final Event.
APRIL 16 — The Final Event
All competitors are invited to attend the final event, which will be held on Thursday, April 16, from 6:00–9:00 pm, in person in the Interdisciplinary Life Sciences Building (ILSB) auditorium with remote participation via Zoom (the event link will be available through Canvas). Drinks and snacks will be provided for in-person attendees. Finalist teams will have ten (10) minutes to present to the judging panel, with an additional five (5) minutes for Q&A. Judges will review and select the winning teams based on their written reports and presentations. The competition winners will be announced at the final event, along with special team prizes.
Competition Rules
TAMIDS’s Student Data Challenge is an open-ended data science competition where teams identify a goal and develop a final report and presentation. Visit the competition rules page for a full explanation of the rules.
The Data Challenge is held over seven weeks, starting with the Kick-Off Session (February 26) and ending with theFinal Event (April 16). All competitors have five (5) weeks to conduct their analysis, write a report, and submit it by the deadline. Selected finalists will be invited to give a presentation before a panel of judges during the Final Event.
Full Competition Rules
All teams should:
- Identify a community, stakeholder, or impacted group: Every organization needs to make informed decisions to achieve its goals. Teams must identify a specific target stakeholder that will be impacted by their data analysis.
- Conduct Descriptive, Diagnostic, Predictive, or Prescriptive Analytics: Using the provided dataset and other publicly available data, teams will examine data to answer questions, identify trends, and extract insights.
- Communication with End-users: Competitors should aim to inform non-technical leaders and stakeholders about their data analysis and to help them formulate strategies, make decisions, or take specific actions.
Prizes
Midpoint Prizes
Best Visualization: $250
Final Event Prizes
Graduate Division
First Placed Team: $2,000
Second Place Team: $1,000
Third Place Team: $500
Undergraduate Division
First Placed Team: $2,000
Second Place Team: $1,000
Third Place Team: $500
Special Team Prizes
Best Presentation Design: $500
Best Use of Additional Data: $500
Best Supplementary Materials: $500
Competition Organizing Committee
Drew Casey; Associate Director for Program Engagement, Texas A&M Institute of Data Science; drew.casey@tamu.edu
Jennifer Cutler; Associate Director for Industry Engagement, Texas A&M Institute of Data Science; jenniferjoe@tamu.edu
Nick Duffield; Director of Texas A&M Institute of Data Science, Professor, Department of Electrical and Computer Engineering; duffieldng@exchange.tamu.edu
Jonathan Jensen; Professor, Department of Kinesiology & Sport Management, Associate Director, Center for Sport Management Research and Education (CSMRE); jajensen@tamu.edu
Steven Riechman; Professor, Kinesiology and Sport Management; sriechman@tamu.edu
Hadi Salman; TAMIDS Knowledge Development Fellow, Instructional Assistant Professor, Department of Statistics; hadi.salman@tamu.edu
Jian Tao; Assistant Director for Project Development & TAMIDS Digital Twin Lab Director, Assistant Professor, Visual Computing and Creative Media Section (College of Performance, Visualization, & Fine Arts); jtao@tamu.edu
Sponsors
Texas A&M Institute of Data Science