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I'm bored

temery said:
How do you think AI will be used in college sports?
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AI will be used in college sports for performance optimization, recruiting, and strategic analysis through tools that track athlete metrics, analyze game footage, and create personalized training plans. Beyond the field, AI will help with academic and career-related tasks, data-driven fan engagement, and automated aspects of officiating.

Athlete performance and health
  • Performance tracking: AI systems with sensors and cameras can track an athlete's movement, physiology, and performance in real-time to provide immediate feedback.
  • Personalized training: AI can analyze vast datasets to create customized training programs that target specific strengths and weaknesses, as well as help monitor nutrition and identify injury risks.
  • Injury prevention: By analyzing training data, game data, and other health metrics, AI can help predict and prevent injuries before they occur.
Recruiting and strategy
  • Player evaluation: AI can evaluate a recruit's statistics, physical qualities, mental toughness, and consistency from video footage and data, helping coaches build a more comprehensive profile.
  • Recruiting models: AI can model ideal player profiles that fit a specific team's system, helping coaches narrow in on targets more effectively.
  • Game strategy: Predictive analytics allow coaches to analyze historical data, opponent behavior, and game conditions to optimize strategies and make in-game adjustments.
Operations and other support
  • Game analysis: AI-powered platforms can automatically tag and analyze game footage, breaking down plays, routes, and formations in seconds, freeing up coaches to focus on coaching.
  • Academic and career support: AI can assist with academic monitoring, degree progress, and even career readiness, providing a more holistic view of a student-athlete's success.
  • Automated officiating: AI could be used to assist with officiating to reduce human error and improve fairness in calls.
  • Fan engagement: AI can help sports media departments create new and exciting fan experiences, from personalized content to virtual reality scenarios.
😉
 
storrsroars said:
AI will be used in college sports for performance optimization, recruiting, and strategic analysis through tools that track athlete metrics, analyze game footage, and create personalized training plans. Beyond the field, AI will help with academic and career-related tasks, data-driven fan engagement, and automated aspects of officiating.

Athlete performance and health
  • Performance tracking: AI systems with sensors and cameras can track an athlete's movement, physiology, and performance in real-time to provide immediate feedback.
  • Personalized training: AI can analyze vast datasets to create customized training programs that target specific strengths and weaknesses, as well as help monitor nutrition and identify injury risks.
  • Injury prevention: By analyzing training data, game data, and other health metrics, AI can help predict and prevent injuries before they occur.
Recruiting and strategy
  • Player evaluation: AI can evaluate a recruit's statistics, physical qualities, mental toughness, and consistency from video footage and data, helping coaches build a more comprehensive profile.
  • Recruiting models: AI can model ideal player profiles that fit a specific team's system, helping coaches narrow in on targets more effectively.
  • Game strategy: Predictive analytics allow coaches to analyze historical data, opponent behavior, and game conditions to optimize strategies and make in-game adjustments.
Operations and other support
  • Game analysis: AI-powered platforms can automatically tag and analyze game footage, breaking down plays, routes, and formations in seconds, freeing up coaches to focus on coaching.
  • Academic and career support: AI can assist with academic monitoring, degree progress, and even career readiness, providing a more holistic view of a student-athlete's success.
  • Automated officiating: AI could be used to assist with officiating to reduce human error and improve fairness in calls.
  • Fan engagement: AI can help sports media departments create new and exciting fan experiences, from personalized content to virtual reality scenarios.
😉
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You just used AI to answer a question about AI? Well done.
 
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storrsroars said:
AI will be used in college sports for performance optimization, recruiting, and strategic analysis through tools that track athlete metrics, analyze game footage, and create personalized training plans. Beyond the field, AI will help with academic and career-related tasks, data-driven fan engagement, and automated aspects of officiating.

Athlete performance and health
  • Performance tracking: AI systems with sensors and cameras can track an athlete's movement, physiology, and performance in real-time to provide immediate feedback.
  • Personalized training: AI can analyze vast datasets to create customized training programs that target specific strengths and weaknesses, as well as help monitor nutrition and identify injury risks.
  • Injury prevention: By analyzing training data, game data, and other health metrics, AI can help predict and prevent injuries before they occur.
Recruiting and strategy
  • Player evaluation: AI can evaluate a recruit's statistics, physical qualities, mental toughness, and consistency from video footage and data, helping coaches build a more comprehensive profile.
  • Recruiting models: AI can model ideal player profiles that fit a specific team's system, helping coaches narrow in on targets more effectively.
  • Game strategy: Predictive analytics allow coaches to analyze historical data, opponent behavior, and game conditions to optimize strategies and make in-game adjustments.
Operations and other support
  • Game analysis: AI-powered platforms can automatically tag and analyze game footage, breaking down plays, routes, and formations in seconds, freeing up coaches to focus on coaching.
  • Academic and career support: AI can assist with academic monitoring, degree progress, and even career readiness, providing a more holistic view of a student-athlete's success.
  • Automated officiating: AI could be used to assist with officiating to reduce human error and improve fairness in calls.
  • Fan engagement: AI can help sports media departments create new and exciting fan experiences, from personalized content to virtual reality scenarios.
😉
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AI is getting pretty devious. It comes up with a bunch of “wow thats amazing” theoretical stuff (preventing injuties before they happen) and omits the most likely thing it will really be used for: dynamic ticket prices individually calibrated to squeeze the maximum amout of dollars out of every fans pocket.

And individually tailored pleas to donors based on their internet behavior.
 
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I would opt in for AI immediately if it could have ended the Tenn/Cuse game 15 minutes earlier on Tuesday night
Podcast What GIF by Washed Media
 
I think training and health will be insane using AI. I have a Whoop band and it's really life changing even for a short old fat guy. I can't imagine how the data could be used for a high performance athlete.
 
Not sure if AI or just analytics in general but let’s use the computers for rankings. Especially for postseason tournaments. College football is the worst at the moment. It’s clear that these committees are corrupted by bias. The BCS days were way better.
 
UConnTrumbull said:
Not sure if AI or just analytics in general but let’s use the computers for rankings. Especially for postseason tournaments. College football is the worst at the moment. It’s clear that these committees are corrupted by bias. The BCS days were way better.
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That presumes that the initial algorithms wouldn't bake in that same bias. I'm pretty confident that they would.
 
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Deepster said:
I think training and health will be insane using AI. I have a Whoop band and it's really life changing even for a short old fat guy. I can't imagine how the data could be used for a high performance athlete.
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I had to google the whoop band. How much is the monthly subscription?
 
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Screenshot_20251204_101246_Google.jpg
 
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John said:
we won't have to worry about college sports once Skynet takes over.
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Yeah, but could you imagine a football or basketball game played by two teams of terminators.
 
storrsroars said:
AI will be used in college sports for performance optimization, recruiting, and strategic analysis through tools that track athlete metrics, analyze game footage, and create personalized training plans. Beyond the field, AI will help with academic and career-related tasks, data-driven fan engagement, and automated aspects of officiating.

Athlete performance and health
  • Performance tracking: AI systems with sensors and cameras can track an athlete's movement, physiology, and performance in real-time to provide immediate feedback.
  • Personalized training: AI can analyze vast datasets to create customized training programs that target specific strengths and weaknesses, as well as help monitor nutrition and identify injury risks.
  • Injury prevention: By analyzing training data, game data, and other health metrics, AI can help predict and prevent injuries before they occur.
Recruiting and strategy
  • Player evaluation: AI can evaluate a recruit's statistics, physical qualities, mental toughness, and consistency from video footage and data, helping coaches build a more comprehensive profile.
  • Recruiting models: AI can model ideal player profiles that fit a specific team's system, helping coaches narrow in on targets more effectively.
  • Game strategy: Predictive analytics allow coaches to analyze historical data, opponent behavior, and game conditions to optimize strategies and make in-game adjustments.
Operations and other support
  • Game analysis: AI-powered platforms can automatically tag and analyze game footage, breaking down plays, routes, and formations in seconds, freeing up coaches to focus on coaching.
  • Academic and career support: AI can assist with academic monitoring, degree progress, and even career readiness, providing a more holistic view of a student-athlete's success.
  • Automated officiating: AI could be used to assist with officiating to reduce human error and improve fairness in calls.
  • Fan engagement: AI can help sports media departments create new and exciting fan experiences, from personalized content to virtual reality scenarios.
😉
Expand ...

Great comments. Here are my original thoughts.

AI is already starting to reshape college sports, and over the next few years its impact will grow a lot. Here are the biggest ways it’s likely to be used:​


1. Performance Analysis & Player Development​

  • Automated film breakdown: AI can tag plays, recognize formations, identify tendencies, and provide instant scouting insights that used to take hours of staff time.
  • Personalized training plans: Models can analyze biometric data (GPS trackers, wearables, force plates) to tailor workouts and skill development to each athlete.
  • Technique correction: Computer vision tools can break down shooting mechanics, pitching form, sprint gait, etc., offering real-time feedback.

2. Injury Prevention & Sports Medicine​

  • Workload monitoring: AI can spot patterns that predict fatigue or injury risk before humans notice them.
  • Return-to-play modeling: Data from rehab sessions can help trainers know when an athlete is ready to compete safely.

3. Recruiting & Roster Management​

  • Talent identification: AI can compare prospective recruits’ stats and film to historical data to find undervalued players.
  • Transfer portal navigation: With thousands of players moving each year, AI tools can help coaches identify the best fit.

4. Game Strategy & Scouting​

  • Opponent analysis: AI can recognize strategic tendencies (e.g., “they run this play 80% of the time on 3rd and short”).
  • Predictive modeling: Some teams may use simulation tools to test game plans or anticipate how opponents will react.

5. Fan Engagement & Business Operations​

  • Personalized content: AI-generated highlights, tailored social media clips, or real-time game stats for fans.
  • Ticketing and attendance optimization: Predicting demand, dynamic pricing, and improving game-day logistics.

6. Academic Support​

  • While still regulated heavily for fairness, AI tutors and study tools will probably become part of athlete academic support centers.

7. Compliance & Administration​

  • Monitoring NIL activities, flagging potential violations, and managing complex NCAA rulesets.
If you want, I can also:

  • give predictions for 5–10 years from now,
  • compare AI use in D1 vs D2 vs D3,
  • or describe how specific sports (football, basketball, baseball, etc.) may use AI differently.
 
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Football aside, I'm hoping Tom can find an AI plug in for the BY that will pop up and say, "Hey, stop typing, one or more people have already posted the exact same thing in this thread."
 
storrsroars said:
Football aside, I'm hoping Tom can find an AI plug in for the BY that will pop up and say, "Hey, stop typing, one or more people have already posted the exact same thing in this thread."
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In a small way that's already done. When you type a response and look at the bottom, it tells you if there's similar post have been made.

Edit: apparently it only works for thread starters not rep replies to already established threads.
 
storrsroars said:
AI will be used in college sports for performance optimization, recruiting, and strategic analysis through tools that track athlete metrics, analyze game footage, and create personalized training plans. Beyond the field, AI will help with academic and career-related tasks, data-driven fan engagement, and automated aspects of officiating.

Athlete performance and health
  • Performance tracking: AI systems with sensors and cameras can track an athlete's movement, physiology, and performance in real-time to provide immediate feedback.
  • Personalized training: AI can analyze vast datasets to create customized training programs that target specific strengths and weaknesses, as well as help monitor nutrition and identify injury risks.
  • Injury prevention: By analyzing training data, game data, and other health metrics, AI can help predict and prevent injuries before they occur.
Recruiting and strategy
  • Player evaluation: AI can evaluate a recruit's statistics, physical qualities, mental toughness, and consistency from video footage and data, helping coaches build a more comprehensive profile.
  • Recruiting models: AI can model ideal player profiles that fit a specific team's system, helping coaches narrow in on targets more effectively.
  • Game strategy: Predictive analytics allow coaches to analyze historical data, opponent behavior, and game conditions to optimize strategies and make in-game adjustments.
Operations and other support
  • Game analysis: AI-powered platforms can automatically tag and analyze game footage, breaking down plays, routes, and formations in seconds, freeing up coaches to focus on coaching.
  • Academic and career support: AI can assist with academic monitoring, degree progress, and even career readiness, providing a more holistic view of a student-athlete's success.
  • Automated officiating: AI could be used to assist with officiating to reduce human error and improve fairness in calls.
  • Fan engagement: AI can help sports media departments create new and exciting fan experiences, from personalized content to virtual reality scenarios.
😉
Expand ...
How do you think AI will be used in the BY? Nice job at @storrsroars
 
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I like the answers about analyzing strategy and providing feedback about what works. But it sounds tricky. I suspect the current models are not trained on this information.... yet.

Analyzing 2-3 hours of video takes a decent amount of processing. That's problem one. but conceptually easy to solve. Just big fast computers with the best GPUs available. Latest NVIDIA stuff.

Then you need to train AI to understand basketball. Most of the AI models/platforms common people are using are pre-trained models trained on lots of stuff. Basketball is likely not one of them. I mean, AI probably knows all the language, down-screen, horns, A-set, etc.... And it could probably explain in words each concept. Or find video examples of basically all basketball concepts. Both defensive and offensive. That information is all over the internet and thus AI knows it. And knows how to find it.

But can you give AI a video of an offensive set (or defensive) and actually make sense out of it. Can AI identify what sets/plays/defense/etc... are being run. I'm sure all this could be done. But I suspect current models have not been trained with this information. One version of a down-screen or a horns set can look a bit different from another. Can it identify if defense is "switching everything" or not. These things are not easily identifiable. Again, all possible, but I suspect current models are not trained to on this.
 
Asked AI if UConn played well against Kansas. I think the Chief’s briefs may soon be replaced. Or is he really an AI imposter? Was surprised that it said Ross played some minutes at pg? Don’t recall seeing that. He was playing the 2 at times from what I recall.

AI Overview


+3



Yes, UConn played well enough to win against Kansas, securing a 61-56 road victory despite not always playing at their best. The Huskies excelled in key areas, particularly in the second half, where they dominated the rebounding battle, limited Kansas's shooting, and had strong performances from players like freshman Braylon Mullins.
You can watch this video to see highlights of the game and Mullins' performance:

UConn Huskies
https://www.youtube.com/watch?v=6eMP_t2dCbw&t=248
YouTube • Dec 3, 2025
  • Second-half dominance: UConn out-rebounded Kansas 25-10 in the second half and held the Jayhawks to just 25% shooting in the final 20 minutes.
  • Strong individual performances: Braylon Mullins was a breakout star, scoring 17 points, including clutch free throws to seal the win. Other players like Solo Ball also stepped up, with Jayden Ross effectively handling point guard duties when needed.
  • Key plays: The Huskies' defense was sound, especially in the final moments, and Mullins' put-back of a missed shot was a crucial play that helped secure the win.
  • Overall performance: While the offense wasn't at its peak, the team demonstrated resilience and the ability to win in a tough environment, a hallmark of championship-level teams.
 
DW1361 said:
Asked AI if UConn played well against Kansas. I think the Chief’s briefs may soon be replaced. Or is he really an AI imposter? Was surprised that it said Ross played some minutes at pg? Don’t recall seeing that. He was playing the 2 at times from what I recall.

AI Overview


+3



Yes, UConn played well enough to win against Kansas, securing a 61-56 road victory despite not always playing at their best. The Huskies excelled in key areas, particularly in the second half, where they dominated the rebounding battle, limited Kansas's shooting, and had strong performances from players like freshman Braylon Mullins.
You can watch this video to see highlights of the game and Mullins' performance:

UConn Huskies

YouTube • Dec 3, 2025
  • Second-half dominance: UConn out-rebounded Kansas 25-10 in the second half and held the Jayhawks to just 25% shooting in the final 20 minutes.
  • Strong individual performances: Braylon Mullins was a breakout star, scoring 17 points, including clutch free throws to seal the win. Other players like Solo Ball also stepped up, with Jayden Ross effectively handling point guard duties when needed.
  • Key plays: The Huskies' defense was sound, especially in the final moments, and Mullins' put-back of a missed shot was a crucial play that helped secure the win.
  • Overall performance: While the offense wasn't at its peak, the team demonstrated resilience and the ability to win in a tough environment, a hallmark of championship-level teams.
Expand ...

Maybe we need to start a new post game thread authored by AI with a fancy name like Chief and Richz have. Any suggestions?
 
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