I'm bored | The Boneyard
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I'm bored

How do you think AI will be used in college sports?
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.
😉
 
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.
😉

You just used AI to answer a question about AI? Well done.
 
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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.
😉

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.
 
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.
That presumes that the initial algorithms wouldn't bake in that same bias. I'm pretty confident that they would.
 
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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.

I had to google the whoop band. How much is the monthly subscription?
 
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we won't have to worry about college sports once Skynet takes over.
Yeah, but could you imagine a football or basketball game played by two teams of terminators.
 
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.
😉

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."
 
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."

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.
 
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.
😉
How do you think AI will be used in the BY? Nice job at @storrsroars
 
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