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Sooners Ready for More Talent from Cali?

by: Josh McCuistion6 hours agoJosh_Scoop

Oklahoma’s presence in California over the last six months has been to a level the Sooners haven’t seen since the days of Tony Jefferson, Brennan Clay, and Kenny Stills. They’ll hope to keep that run going on Sunday when Inglewood, Calif. defensive lineman Elija Harmon makes his college announcement.

The big man was in Norman for Oklahoma’s 17-13 win over LSU last weekend for his second trip to campus for the season. In both cases Harmon gave the Sooners strong reviews and with Oklahoma having the last word in his recruitment as well as doing a strong job pursuing the nation’s No. 152 player and No. 17 defensive lineman, in the Rivals industry ranking, it’s time to put in a prediction for Oklahoma.

The win would be a big one for the Sooners as he’d join Krew Jones on the defensive line as well as Cooper Hackett, Kaeden Penny, and Luke Wilson on the offensive line as the Sooners pour a lot of focus into adding high-end talent in the trenches.

Highlights of On3’s Recruiting Prediction Machine:

  • Combines data and expert predictions on an AI platform.
  • V1 release December 2021 with V2 scheduled in Q2 of 2022
  • Algorithm is built to learn from past results; therefore, accuracy will continue to improve over time.
    • For example, it has the capabilities to learn trends like a coach’s success (or lack thereof) with a specific high school or region, the importance of an unofficial visit, and how valuable social media sentiment really is.
  • On3 is removing the manually controlled  “school interest” section with the RPM prediction.

Expertise and data used for the RPM algorithm:

  • Insight and inputted predictions from industry experts:
    • On3 National Recruiting Insiders
    • On3 Fan Site Recruiting Insiders
    • Industry experts with proven track records (Outside of On3 staff)
  • Visits (by the player and by coaches):
    • Official Visits 
    • Unofficial Visits
    • Coaches Visits
  • Sentiment, analyzed by machine-learning:
    • Social sentiment from the athlete
    • Media sentiment
  • Data of previous related outcomes:
    • Geographic Data
    • Coaching Staff historical data
    • State historical data
    • High School historical data

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