June 14, 2012
By Ian Levy
Player comparisons are the shorthand of draft scouting, a way of putting a large amount of information into the smallest possible package. From looking at a player’s best case or worst case scenarios, to comparing a specific trait like length or a jumpshot, player comparisons communicate volumes about how a prospect is perceived and valued. Unfortunately, the information being communicated can be just as arbitrary or inaccurate in describing a player’s future as every other piece of the scouting apparatus. The Holy Grail, of course is to be able to not just fine-tune player comparisons, but massage them into accurate projections of statistical production. I’ve been working on both projects at Hickory-High.com.
My first contribution was Similarity Scores, a system for creating player comparisons based on statistical production. Turning those comparisons into projections is still a work in progress, but a firm foothold has materialized. In preparing those player Similarity Scores, I amassed a fairly large collection of statistics on recent draft prospects. It was very easy to then compare that college production to NBA production. By running a correlation between the college performance and NBA performance in each statistical category I was able to create a fairly clear picture of what skills most consistently carry over into the NBA. Here are the categories and correlations.
1. Ast/40 _ 0.877
2. Blk/40 _ 0.875
3. OReb/40 _ 0.859
4. FGA _ 0.838
5. DReb/40 _ 0.836
6. 3PTA/FGA _ 0.827
7. Stl/40 _ 0.750
8. FT% _ 0.714
9. PF/40 _ 0.656
10. 3PT% _ 0.622
11. FTA/40 _ 0.544
12. TO/Pos _ 0.530
13. Pts/40 _ 0.370
14. TO/Pos _ 0.530
15. USG% _ 0.276
16. Min/G _ 0.118
The closer a correlation is to 1.000 the more consistently that statistic translated from college to the NBA. Unsurprisingly, USG% and Min/G varied the most as the majority of players see their role change significantly as they become pros. Assists, rebounding, shot blocking and steals, were statistics that translated very well. So, looking at this year’s draft prospects, what statistical contributions can you count on?
Tyler Zeller on the Offensive Glass
Offensive Rebounding is a statistical contribution that has carried over very well for most players. This bodes very well for the future of Tyler Zeller.
Zeller averaged 5.0 OReb/40 at North Carolina this past season. Over the past five drafts, nine different college players have entered the NBA having averaged at least 5.0 OReb/40 their last season in college – Kevin Love, Joey Dorsey, Jordan Hill, Jon Brockman, DeJuan Blair, DeMarcus Cousins, Al Farouq-Aminu, Kenneth Faried and Josh Harrellson. While not all of those players have gone on to stardom, all have continued to do work on the offensive glass. In 2011-2012 Aminu, who has played mostly small forward in the NBA, had the 97thhighest ORB% among all players at 7.8%. Love, Harrellson, Cousins, Faried, Blair and Hill all ranked in the top 50 in ORB% last season. Dorsey didn’t play in the NBA in 2011-2012, and Brockman played just 239 minutes, but they have career ORB% of 17.2% and 15.2%. Great offensive rebounders in college become great offensive rebounders in the NBA.
Zeller’s shooting prowess and ability to run the floor, should earn him consistent minutes, even early on in his career. Whatever team selects him on draft night should also be able to count on him effectively crashing the offensive glass when he is on the floor.
Kendall Marshall and Scott Machado Facilitating Offense
Both Machado and Marshall averaged over 10.0 Ast/40 this season, a statistic milestone that makes this year’s point guard draft pool exceedingly rare. You have to go all the way back to T.J. Ford in 2001-2002, although he didn’t leave Texas until after the 2002-2003 season, to find another legitimate NBA prospect who passed that 10.0 Ast/40 plateau. The basketball contributions of Marshall and Machado aren’t just elevated by their passing, they’re defined by it - both players had more assists last season than field goal attempts.
As you can see from the list above both a player’s willingness to pass, and success in creating shots for their teammates, are skills that translate very well from college to the pros. Although not to the level of Machado and Marshall, several players have been drafted in the past decade with gaudy assist totals. Those who have carved out NBA careers like Chris Paul, Deron Williams, Ty Lawson and Mike Conley, have done so because they augment their passing with efficient scoring, elite athleticism or stout defense. Others like Marcus Williams or T.J. Ford have found their NBA careers to be less stable or nonexistent because they didn’t have offer enough production in other areas to supplement their passing.
When Marshall and Machado are on the floor they will find open teammates, of that there is no doubt. The question is if they can provide enough production in other areas to earn consistent minutes.
Anthony Davis Defending the Rim
Anyone who watched Davis this season at Kentucky knows he is a premier shot-blocker. Blocked shots is another form of statistical production that translates very well from college to the pros, but plenty of premier college shot blockers haven’t been able to work their way into NBA rotations. Jarvis Varnado, Hassan Whiteside and Sean Williams all left college averaging more Blk/40 minutes than Davis, but none has made an impact.
However, Davis has a skill that none of those three possessed – blocking shots without fouling. All three of those players averaged at least 3.0 PF, while Davis committed just 2.4. With his 5.8 Blk/40, Davis blocked 2.4 shots for every personal foul he committed. That’s the best ratio of any collegiate draft prospect over the last decade. Davis will likely be more successful because of his potential for greater diversity in his contributions than Whiteside, Varnado, or Williams. But he also has the potential to wreak more havoc with his shot blocking than any of those three.
When the Hornets grab Anthony Davis with the top pick they can count on not just his game-changing defensive ability, but also his ability to stay out of foul trouble while he does it.
*All per 40 minutes statistics cited in this piece are pace adjusted