Sports
The Real Impact of AI in Sports: 5 Things You Haven’t Heard
David Evans is an experienced sports journalist with over 15 years in the field. He is known for his reliable and insightful commentary, which has been featured on numerous top sports betting platforms. David specializes in North Carolina basketball, college football, the NFL, soccer, and golf, offering deep knowledge and straightforward analysis in his articles. Outside of work, David stays active with regular gym workouts and enjoys relaxing at home with his cat. With a solid blend of experience and passion, David is a well-respected name in sports journalism, consistently providing valuable and informative content to his readers.
Get to know David Evans betterPublished07 Apr 2025
AI in sports isn’t just about instant replays or automated offsides. The real impact is happening where fans can’t see it—inside helmets, under jerseys, and in coaches’ decision-making tools. Here are five low-profile ways AI is reshaping the way games are played, coached, and managed.
1. AI Is Telling Coaches When to Sub Players
Teams are no longer guessing when a player is gassed.
AI models pull in data like heart rate, speed, work rate, and in-game context to flag players who are about to break down or fade.
Tools like Zone7 generate live substitution alerts: “If you don’t take Player X out soon, he’s going to make a mistake or pull a hamstring.”
Used across soccer, rugby, and increasingly in college sports where depth matters.
2. Smart Gum Shields Are Helping Prevent Concussions
Rugby and Aussie Rules are testing AI-enabled mouthguards to detect high-impact collisions in order to reduce concussions.
They measure force, direction, and frequency of impacts in real time.
When a threshold is hit, medical staff get an alert to assess the player—even if no one saw the hit.
NFL has been trialing helmet sensors, but smart gum shields may offer better data on head trauma during practices and lower-level games.
3. Teams Are Using Betting Models to Measure Strategy
Some sports teams are now reverse-engineering betting market data from top sportsbooks.
Soccer teams are monitoring expected goals, possession, and other metrics vs. live odds to see how outside models interpret their decisions.
If betting markets consistently undervalue their approach, that’s useful feedback—or a sign they’re tactically ahead.
This isn’t public-facing, but several European soccer clubs and at least one college football program are experimenting with it.
4. Ball Flight and Spin Are Being Tracked Without Sensors
AI-enhanced cameras now track every detail of the ball’s movement.
In baseball, systems like Hawk-Eye and Rapsodo monitor pitch velocity, spin axis, and break—all without any physical chips or sensors.
In soccer, similar systems analyze shot curve, dip, and keeper reaction times for scouting and player development.
It’s helping hitters and pitchers make micro-adjustments based on real physics, not guesswork.
5. AI Is Quietly Building Better Offensive Lines
Some NFL teams are using computer vision to grade offensive line play frame-by-frame.
Traditional grading is at least somewhat subjective. AI tools analyze hand placement, leverage, movement efficiency, and pocket integrity.
This helps line coaches spot patterns in protection failures and identify undervalued linemen in film review.
This type of tool is also being used in college recruiting to scout technique at scale.
Final Word
AI isn’t flashy in sports. It’s invisible, fast, and mostly quiet. But it’s making coaching smarter, players safer, and front offices more precise. Most fans won’t notice it—but teams already rely on it every day.
