I've updated the formula slightly* since I wrote the essay for the College Basketball Prospectus preview this year. Offensive Ratings, usage, and strength of schedule all from kenpom.com.
Offensive impact estimates how much a player's contributions (by usage & efficiency) impact his team's offense above average (i.e. a +13 player would make an average team score 1.13 PPP, if the league average was 1 PPP).
|Player||Team||Year||ORTG||%USG||adjusted Offensive Impact|
|2||Damian Lillard||Weber St.||Jr||125.7||31.7||12.8|
|7||Anthony Drmic||Boise St.||Fr||135.4||24.2||11.0|
|9||Tahj Tate||Delaware St.||Fr||120.8||31.2||10.9|
I expect more Major-Conference heavy hitters to top this list soon. We've all taken the oath of small sample sizes here, right?
I don't feel comfortable sharing more than the top-10 because many players with Top-50 Offensive Impact numbers are cut out by not having high enough Offensive Ratings (for example: Jordan Taylor, at least at the moment) to be grouped on Pomeroy's site. But I don't have the time to input every NCAA player manually.
The coefficients for ORTG, Usage, and ORTG*Usage are still the same, but I used a more theory-based adjustment for strength of schedule. Also I added a term that helps predict team ORTG better (the numbers were too small so each player gets boosted by 1ish).