I’m a bit of a stats geek. I like playing around with numbers and seeing what I can learn. Maybe it’s the engineer side of me. When it comes to evaluating basketball performance, the standard measures like points, rebounds or assists per game just don’t do a good enough job. They isolate only one aspect of the game.
That’s why I like some of the various player rating systems like Tendex or Prouty. You can read a bit about these calculations here. I like the Prouty in particular, because it takes the team’s overall record into account. While that may not be a great measure of individual contribution, it helps fill the gaps for all the things basketball players do to help their team win that don’t show up in the box score, like setting a good screen, boxing out, fighting through screens, diving for loose balls, etc. If a team has players doing those things, they’ll likely be more successful and that will be reflected in part in the overall team record.
The whole Prouty calculation is this: [{Points / (Field Goals Attempted*2 + FTA)} + {(Points + Assists*2 – Turnovers) / Minutes} + {(Rebounds + Steals + (Blocks/2) – Personal Fouls) / Minutes} + {(Minutes / (TEAM TOTAL Minutes / 5)) * Team Winning Pct} ] / 4
If you look closely, you’ll see that there are four main sections. I’ll call them Offensive Efficiency (how many points you score per shot), Points Per Minute (how many points you score or help others score per minute), Possessions Per Minute (how many possessions you gain or lose your team per minute) and Win Effect (how responsible you are to your team’s win percentage, based on minutes per game).
As you can see, it factors in most items in the box score, points, rebounds, assists, steals, turnovers, fouls, etc. as well as some efficiency ratios. All-in-all, I think it does a good job of identifying those players who do the most to help their teams win.
At this point of the season, most of the pre-conference games are done. There may be a cupcake or two left on some schedules, but basically the first part of the season is over. Now seems like a good time to see who’s had the best start to the season. I’ll check back later in the year using only conference games to make things more fair, but for now, we just have to live with the fact that teams have played very different schedules.
So without further ado, here are your top 50 ACC players as ranked by Prouty:
Rank | Player | Team | Prouty |
1 | Julius Hodge | NCSU | 0.605 |
2 | JJ Redick | Duke | 0.576 |
3 | Sean May | UNC | 0.572 |
4 | Daniel Ewing | Duke | 0.568 |
5 | John Gilchrist | MD | 0.564 |
6 | Chris Paul | WF | 0.559 |
7 | Shelden Williams | Duke | 0.555 |
8 | Jarrett Jack | GT | 0.552 |
9 | Rashad McCants | UNC | 0.530 |
10 | Jawad Williams | UNC | 0.529 |
11 | Devin Smith | UVA | 0.522 |
12 | Elton Brown | UVA | 0.513 |
13 | Robert Hite | UM | 0.511 |
14 | Raymond Felton | UNC | 0.508 |
15 | Sean Dockery | Duke | 0.495 |
16 | Luke Schenscher | GT | 0.490 |
17 | Chris McCray | MD | 0.480 |
18 | Eric Williams | WF | 0.471 |
19 | Guillermo Diaz | UM | 0.471 |
20 | Justin Gray | WF | 0.469 |
21 | Nik Caner-Medley | MD | 0.462 |
22 | Andrew Brackman | NCSU | 0.461 |
23 | Sharrod Ford | CU | 0.459 |
24 | Tony Bethel | NCSU | 0.458 |
25 | BJ Elder | GT | 0.458 |
26 | Cliff Hammonds | CU | 0.458 |
27 | Anthony Harris | UM | 0.448 |
28 | Sean Singletary | UVA | 0.448 |
29 | Shawan Robinson | CU | 0.445 |
30 | Jamaal Levy | WF | 0.438 |
31 | Will Bynum | GT | 0.437 |
32 | Isma’il Muhammad | GT | 0.436 |
33 | Jordan Collins | NCSU | 0.436 |
34 | JR Reynolds | UVA | 0.435 |
35 | Taron Downey | WF | 0.428 |
36 | Zabian Dowdell | VT | 0.425 |
37 | Marvin Williams | UNC | 0.424 |
38 | David Noel | UNC | 0.421 |
39 | Travis Garrison | MD | 0.420 |
40 | DeMarcus Nelson | Duke | 0.417 |
41 | Carlos Dixon | VT | 0.413 |
42 | Cameron Bennerman | NCSU | 0.411 |
43 | Ra’Sean Dickey | GT | 0.410 |
44 | Anthony King | UM | 0.405 |
45 | Akin Akingbala | CU | 0.404 |
46 | DJ Strawberry | MD | 0.402 |
47 | Anthony McHenry | GT | 0.400 |
48 | Ilian Evtimov | NCSU | 0.394 |
49 | Shavlik Randolph | Duke | 0.393 |
50 | Ekene Ibekwe | MD | 0.393 |
At first glance, it looks like the ratings came about pretty close to what I expected. The guys at the top are generally considered the top players in the league. That’s a pretty good sign that the rating system is effective. It should produce reasonable results, but still help you to maybe see some nuances you wouldn’t otherwise pick up on.
I was surprised a bit to see McCants so low. I figured he’d be in the top three. It seems that what hurts him is his high number of fouls. Only Eric Williams in the top twenty has committed more fouls (30) than McCants’ 28. When your foul total is comparable to Eric Williams’, well, you have some work to do.
Conversely, I was also a bit startled to see Nick Caner-Medley up at number 22. From the heat he’s been taking from Maryland fans online, I’d have pegged him for much lower. Maybe they need to back off him a bit. Sure, his misses and turnovers tend to be dramatic, but overall, he’s the third most effective Terrapin.
I’ll put the whole table with the raw source data in a separate file here.
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