Picture a college esports coach hunched over their desk at midnight, scrubbing through their third consecutive hour of Valorant gameplay footage. They’re searching for that split-second positioning error that cost their team the round, trying to spot patterns across dozens of matches while juggling spreadsheets and handwritten notes. Tomorrow they’ll need to do it all over again—for a different team, in a different game.
“Limited feedback was a huge problem,” admits Jared Connell, former coach at Graceland University and now working with multiple esports startups. “As a coach, you’re trying to give feedback to multiple teams across multiple games, and it’s just overwhelming.”
This exhausting reality—coaches spending upwards of 50 hours weekly reviewing gameplay, yet still missing crucial insights—was the catalyst for a recent Esports Trade Association discussion on how artificial intelligence is transforming the coaching landscape. Hosted by Shubber Ali, CEO of Omnic.AI, the LinkedIn Live session revealed how the data deluge threatening to drown college esports programs might actually be their greatest opportunity.
Connell witnessed the explosive trajectory of college esports during his transition from competitive wrestler to coach. “When I first went to Graceland, my very first year, I was still a wrestler. They were a club team that trained in our library,” he recalls. “By the time I took over the program, we had invested $25,000 into a whole lab.”
That four-year transformation mirrors a pattern rippling across American campuses. The University of Southern Maine just unveiled a state-of-the-art esports arena. Colorado State University built an established program from nothing in six years. “You saw tons of that growth of just these passionate people sparking up everywhere,” Connell explains. “It’s exponential.”
Feeding this collegiate boom is an even more dramatic expansion at the high school level, where platforms like PlayVS now serve over 10,000 schools. This creates both unprecedented opportunity and a fundamental challenge: How do college programs evaluate this massive influx of talent when human coaches are already maxed out?
Enter artificial intelligence—not as a replacement for human coaches, but as their force multiplier. Omnic.AI’s platform has already processed over 130,000 matches across Valorant, Rocket League, and League of Legends, extracting insights impossible for human eyes to catch.
The AI develops what Connell calls a “fingerprint” for each player—a unique profile of playstyle, habits, and tendencies that becomes more accurate with every match. “As it learns your fingerprint, it learns what your patterns are,” Connell explains. “It gives continuously more accurate feedback—not just about what everyone else is doing, but specifically what you’re doing.”
A ChatGPT-like interface allows players to ask specific questions about their performance—should I use a different weapon here? Am I rotating too slowly?—and receive answers based not just on their own gameplay but on data from tens of thousands of players using similar characters and strategies.
The platform’s most sophisticated element is its ability to segment insights by skill level. “You don’t want to give really basic information to super experienced players,” Ali notes, drawing an analogy to traditional sports. “No one’s telling Serena Williams, ‘okay, you want to throw the ball up and make sure you’re holding your wrist this way.’ She’s got that part figured out.”
Future updates will formalize this tiering, delivering foundational tips to novices while providing advanced players with nuanced adjustments that separate good from great. The AI’s training process reflects this sophistication—an eight-to-twelve-week development phase, followed by beta testing until the system reaches 95% accuracy, then continuous improvement as more players use it.
Throughout the discussion, both Ali and Connell emphasized that AI isn’t displacing human coaches—it’s freeing them to focus on what technology can’t replicate. Coaches build team culture, manage interpersonal dynamics, and provide emotional intelligence. What AI does is eliminate the mechanical grunt work of reviewing endless footage, giving coaches back time to actually coach.
The most successful programs won’t be those that hand everything over to AI, but those that thoughtfully integrate it into their coaching workflow—using automation for data analysis while reserving human expertise for strategy, leadership, and player development.
As the session concluded, one message resonated clearly: AI-powered coaching isn’t emerging technology—it’s current reality. The programs that embrace these tools will gain measurable advantages in talent evaluation, player development, and strategic preparation.
For coaches drowning in VOD reviews and spreadsheet management, the question isn’t whether to explore AI coaching assistance. It’s whether they’ll adopt it before their rivals do.
