New Recruiting Prediction Machine entry for Penn State
Penn State’s coaching staff finds themselves in a strong position so far in the Class of 2023.
With eight players already committed, including one five-star and three four-star players, Penn State ranks among the nation’s best currently. In addition to being No. 5 overall in the On3 Consensus Team Rankings, the Lions are ranked second in the Big Ten, just behind Ohio State, who has five commitments currently. Michigan is also off to a strong start, sitting at No. 8 overall. The Wolverines also sit at five commitments currently.
I also believe that Penn State finds itself in a good position with a handful of coveted players, one of whom is defensive end Mason Robinson from McDonogh. Although he remains unranked currently, make no mistake: Robinson a top target for the Nittany Lions.
Mailbag: When can Penn State fans expect more commitments?
“I just talked to Coach [John] Scott last weekend,” Robinson told BWI in an interview this week. “He’s a very genuine guy. I love seeing African-American coaches thrive and do well for themselves, so we have a good connection.
“We have four McDonogh guys up there, if you include Dani [Dennis-Sutton]. They’ve been after me hard, especially Dani since he committed. It’s a brotherhood up there. I’m not swayed by that, but it is nice having them up there. But right now, Penn State is looking good. I’m planning on going up there at some point in April. I think it’ll be April 8th or the 9th. I plan to check out one of their spring practices.”
Top 10
- 1
LaNorris Sellers
South Carolina QB signs NIL deal to return
- 2New
Justice Haynes
Alabama transfer RB commits
- 3
National Championship odds
Updated odds are in
- 4Trending
Urban Meyer
Coach alarmed by UT fan turnout at OSU
- 5Hot
CFP home games
Steve Spurrier calls for change
Get the On3 Top 10 to your inbox every morning
By clicking "Subscribe to Newsletter", I agree to On3's Privacy Notice, Terms, and use of my personal information described therein.
With Robinson being one of the staff’s top defensive ends, I logged an entry for Penn State to land Robinson in On3’s Recruiting Prediction Machine Saturday afternoon. PSU’s success at McDonogh over the years certainly played a role in that decision. As Robinson mentioned, Penn State has three players from McDonogh currently on its roster: DT PJ Mustipher, DT Dvon Ellies and LB Curtis Jacobs. Dennis-Sutton will become the fourth when he joins them this summer.
Robinson is the sixth RPM prediction I’ve logged in the Class of 2023. He joins wide receivers Kenny Johnson and Rodney Gallagher, as well as linebackers Ta’Mere Robinson, Tony Rojas and Phil Picciotti. I also logged one in the Class of 2024 last week for offensive lineman Peter Jones.
Penn State was already the favorite with Robinson in On3’s RPM, but now the Nittany Lions have jumped from 37.8 percent to 92.5. In addition to Penn State, Robinson also has plans to visit South Carolina in April. He’s tentatively planning for April 2. Pitt and Virginia Tech are also in the mix. All three of those schools have hosted him at least once, although Penn State has hosted him three times now, more than any other school.
Highlights of On3’s Recruiting Prediction Machine
- Combines data and expert predictions on an AI platform.
- V1 released 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 in 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