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ESPN’s NBA success machine does not like anyone on Kentucky’s roster

None of these guys are in the top 30?

By Jamie Boggs
Jamie Boggs - Sea of Blue

If the RPI ratings are not accurate, then we create the NET.

But what about the KenPom? Prefer the eyeball test?

There are so many ways to measure teams and players that sometimes we outthink ourselves when trying to assess the value of a team or individual.

Kevin Pelton of ESPN recently did just that in calculating the first five years of NBA projections based on a variety of measurements. There are a lot of surprises in his list, which only includes the top 30 players according to his formula.

None of those players come from the University of Kentucky.

Statistical Top 30

  1. Zion Williamson, Duke Blue Devils
  2. Ja Morant, Murray State Racers
  3. Cam Reddish, Duke Blue Devils
  4. RJ Barrett, Duke Blue Devils
  5. Bol Bol, Oregon Ducks
  6. Tyrese Haliburton, Iowa State Hawkeyes
  7. Darius Garland, Vanderbilt Commodores
  8. Dedric Lawson, Kansas Jayhawks
  9. Talen Horton-Tucker, Iowa State Hawkeyes
  10. Shamorie Ponds, St. Johns Red Storm
  11. Jarrett Culver, Texas Tech Red Raiders
  12. Chuma Okeke, Auburn Tigers
  13. Jaxson Hayes, Texas Longhorns
  14. De’Andre Hunter, Virginia Cavaliers
  15. Matisse Thybulle, Washington Huskies
  16. Brandon Clarke, Gonzaga Bulldogs
  17. John Konchar, Purdue-Fort Wayne Mastodons
  18. Nickeil Alexander-Walker, Virginia Tech Hokies
  19. Markus Howard, Marquette Golden Eagles
  20. Sam Hauser, Marquette Golden Eagles
  21. Coby White, North Carolina Tar Heels
  22. Romeo Langford, Indiana Hoosiers
  23. Nassir Little, North Carolina Tar Heels
  24. Dylan Windler, Belmont Bruins
  25. Jontay Porter, Missouri Tigers
  26. Kevin Porter Jr., USC Trojans
  27. Ty Jerome, Virginia Cavaliers
  28. Cassius Winston, Michigan State Spartans
  29. Grant Williams, Tennessee Volunteers
  30. Tre Jones, Duke Blue Devils

Peltner uses NCAA performance to predict rookie NBA performance, and then projects that out for five years of NBA performance. He also adds in performance in the Nike EYBL and incorporates an adjustment for wins above replacement projection (WARP) to consider player position.

I am no statistician, but it sounds like he put these projections together in the same way my grandmother used to make stew. A pinch of this, a little of that, and then a cup of that if we have any in the fridge.

The top four picks are actually possible, if you flip Barrett with Reddish. But after that, things seem to get out of hand. You are telling me two Ohio State players project better to the NBA than anyone on Kentucky’s roster? John Konchar of Purdue-Fort Wayne is a better prospect than PJ Washington? Belmont’s Dylan Windler will have a better NBA career than Keldon Johnson?

I am all for statistics. I have a degree in mathematics. But if the result of your analysis makes no sense logically, then your process is flawed.

Check out commentary on these flawed projections here.

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