Skip to main content

Oregon offers 4-star wideout Malik Elzy

PeterWarrenPhoto2by:Peter Warren05/16/22

thepeterwarren

Malik Elzy
(EJ Holland/On3)

Oregon has extended an offer to Chicago Simeon four-star wide receiver Malik Elzy.

He is the No. 386 overall recruit in the 2023 cycle, according to the On3 Consensus, a complete and equally weighted industry-generated average that utilizes all four major recruiting media companies.

Rock Island (Ill.) Alleman offensive tackle Charles Jagusah, East St. Louis (Ill.) four-star offensive tackle Miles McVay, Arthur (Ill.) Arthur Senior four-star linebacker Kaden Feagin, Kankakee (Ill.) four-star four-star athlete Jyaire Hill and Bolingbrook (Ill.) four-star safety Damon Walters are the five players from Illinois ranked ahead of Elzy in the rankings.

He currently has an On3 NIL Valuation of $19.9k. The On3 NIL Valuation is an index that looks to set the standard market value for both high school and college-level athletes. The NIL valuation does not act as a tracker of the value of NIL deals an athlete has completed to date. It rather signifies an athlete’s value at a certain moment in time.

Notre Dame is the favorite for Elzy, according to On3 Recruiting Prediction Machine, with a 34.6% chance of landing Elzy.

Top 10

  1. 1

    DJ Lagway

    Florida QB to return vs. LSU

    Breaking
  2. 2

    Dylan Raiola injury

    Nebraska QB will play vs. USC

  3. 3

    Elko pokes at Kiffin

    A&M coach jokes over kick times

  4. 4

    SEC changes course

    Alcohol sales at SEC Championship Game

    New
  5. 5

    Bryce Underwood

    Michigan prepared to offer No. 1 recruit $10.5M over 4 years

View All

“I have a good connection with Coach [Tommy] Rees, Coach [Dre] Brown and all those guys,” Elzy told Blue & Gold. “Coach Del [Alexander] leaving – it really doesn’t affect the relationship I have with Notre Dame.”

RPM was released to the public in December. The On3 engineering group teamed up with Spiny.ai to create the industry’s first algorithm and machine learning-based product to predict where athletes will attend college. 

It factors in machine learning, expert predictions, social sentiment, visits, and historical trends. However, expert predictions are still a big piece of the RPM equation.