Sooners To Land Two from Natural State?
For two neighboring states it’s largely been one-way traffic in the recruiting world. For years Arkansas has come into Oklahoma to land quality prospects from the Sooner state. Their success has largely come from nearby Tulsa and the Razorbacks have even pulled a few head-to-head wins over the Sooners. Notably among them is former Booker T. Washington superstar Felix Jones.
In 2025 Oklahoma is in true contention with a pair of Arkansas natives, defensive back offers Marcus Wimberly and Omarion Robinson. And though we’ve already discussed the pick of Wimberly, the Sooners have quietly made themselves a very real presence in the recruitment of Robinson. And though he can be quiet and isn’t one to tip his hand in regard to his recruitment too much, he is also someone that is clearly high on the Sooners.
He has built strong relationships with the Oklahoma staff and seems to be developing a real comfort with Norman itself. We’re expecting him to return for another visit at some point in the next few months.
A confidence or 50% was put into the RPM-day pick for the Sooners. To date my success rate has been 86.9-percent with On3 predictions. In the 2025 class I’ve also got Sooners predictions in for Wimberly, Ty Haywood, Jonah Williams, CJ Nickson, Tory Blaylock, Max Granville, Cobey Sellers, Nate Roberts, and Trystan Haynes.
On3 Recruiting Prediction Machine (RPM)
Though On3 expert predictions are a key part of the On3 RPM, they are far from the only information the RPM takes into account. Take a look at a breakdown of all that the algorithm considers as it calculates a school’s likelihood to land a prospect. In this case Oklahoma currently stands as a 88.9-percent favorite for Robinson.
How did that number come about? Here’s an idea of On3’s considerations.
- 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
