Former NFL running back Kenyon Rasheed and his team at EDGE3.ai are revolutionizing college football programs with predictive analytics. They use AI to compare high school players to college athletes, forecast player success and transfers, and guide players in college selection. Partnering with IBM enhances data governance and AI capabilities, adding a new dimension to sports recruiting.
Read more
AI Summary
AI Chapters
Episode notes
auto_awesome
Podcast summary created with Snipd AI
Quick takeaways
EDGE3.ai uses predictive analytics to project high school players' performance in college football programs.
Collaboration with IBM accelerates AI product development for college football recruiting, optimizing processes and enhancing productivity.
Deep dives
Using AI in College Football Recruiting
Edge3 .ai, a startup, is utilizing AI to assist college football coaches in selecting the right players and to aid high school players in finding the ideal college team. With the evolution of college sports regulations and the emphasis on compensating athletes, scholarship allocation has shifted towards more experienced transfers. Edge3 .ai enhances the efficiency of recruiting by assessing high school players against current college athletes and analyzing social data to determine a player's overall value to a college program.
IBM Partnership for AI Development
Edge3 .ai's collaboration with IBM has accelerated the development and deployment of their AI product for college football recruiting. IBM's data resources and expertise have facilitated Edge3 .ai in creating predictive models, analyzing vast amounts of player data, and implementing AI-driven solutions. Through AI applications and data governance, Edge3 .ai aims to optimize recruiting processes, reduce expenses, and enhance productivity for collegiate football programs, illustrating how AI can be transformative for businesses of all sizes.
Former NFL running back Kenyon Rasheed and his partners at EDGE3.ai are creating a product that may revolutionize college football programs nationwide. It compares the performance of high school players to their counterparts in college, using predictive analytics to project how well they’ll perform in college football programs. It also helps high school players identify at which colleges they’re most likely to get an offer. They’re using IBM technology to help ingest reams of unstructured data, govern disclosure of that information and create natural language interfaces for players to query the data.