The best way to predict the future . . .

[42N8Bounce]

... is to know the past.

Hi guys. First time poster. Long time reader.

Over the past few months, I've spent way too much time creating a model to rate the success of college player in the NBA. In short, I've taken over 500 college players that were drafted into the NBA, and rated their NBA success between 0 (bust) and 100 (All Star). I then compared the stats of the college individual (everything from height, class, school, etc.) to the database of player and found the closest statistical matches. I then take a weighted average to predict the success of the college individual.

I used years 2001 thru 2008 as a template to determine the individuals that would be used in the database, and the weighted average values. Using this model, I compared my results to those of the GMs, and found that this model outperformed the GMs by over 7% between 2001 and 2008. Don't get me wrong. This program is not perfect by any means. It picked Adam Morrison as a sure thing at number 1. But it also grabbed Paul Millsap at 6, and Rajon Rondo at 7. Not bad.

I then plugged in this years college draft individuals. I've attached the full results. Here are the top 10:
1. Anthony Davis
2. Jae Crowder
3. John Henson
4. Bradley Beal
5. Michael Kidd-Gilchrist
6. Jeremy Lamb
7. Will Barton
8. Damian Lillard
9. Jared Sullinger
10. Draymond Green

Some others of note:
30. Austin Rivers
36. Andre Drummond
40. Harrison Barnes

These results have a pretty good correlation with many mock drafts. But there are quite a few question marks in there that surprised me.

My favorites for the Blazers - Damian Lillard at 6, and either Sullinger or Zeller at 11. Let me know what you think.

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[Nikolokolus]

Hey welcome ...

I can't wait til HCP sees this.

 

[BrianFromWA]

mixum is back.

Welcome!

 

[Fez Hammersticks]

Hey welcome ...

I can't wait til HCP sees this.

I thought the same thing

Btw, great stuff. Lillard is looking more intriguing by the day.

I agree in Sullinger at #11. His advanced stats speak loud and clear (30 PER; 10WS)

 

[42N8Bounce]

Nope. Definitely not Mixum. I'm from West Linn, OR. Ben a season ticket holder with my family since 1974.

When I started out working on this program, I didn't have much expectations. I was a bit surprised that I was able to create a model that matches up pretty close to a lot of mock drafts. This program certainly can't see "potential". Just the raw stats of what a player has done.

It's all fun.

 

[BrianFromWA]

I'm intrigued, but have some geek questions. Is "bdb score" from your database? And what metric are you using to grade against GMs?

I don't have the time, but I've thought of using a winscore comparison...does your model use hard metrics, either stats-based or things like All-Star games, championships, all-NBA teams, etc?

Also, I wonder what some granularity would do. You have 0 as bust and 100 as all-star, but there HAS to be some difference between, say, All-Star Jamaal Magloire and wannabe All-Stars like James Harden. And then a tier between those guys and MVPs like Rose, and then a tier for all-time greats like K*be and LeBron.

 

[THE HCP]

WHAT IS GOING ON!!!!!!!!!!!!!!!!!!!!!!

 

[THE HCP]

Actually you are setting the bar pretty high if this is your first post my amigo. Nice work!

 

[SlyPokerDog]

... is to know the past.

Hi guys. First time poster. Long time reader.

Over the past few months, I've spent way too much time creating a model to rate the success of college player in the NBA. In short, I've taken over 500 college players that were drafted into the NBA, and rated their NBA success between 0 (bust) and 100 (All Star). I then compared the stats of the college individual (everything from height, class, school, etc.) to the database of player and found the closest statistical matches. I then take a weighted average to predict the success of the college individual.

I used years 2001 thru 2008 as a template to determine the individuals that would be used in the database, and the weighted average values. Using this model, I compared my results to those of the GMs, and found that this model outperformed the GMs by over 7% between 2001 and 2008. Don't get me wrong. This program is not perfect by any means. It picked Adam Morrison as a sure thing at number 1. But it also grabbed Paul Millsap at 6, and Rajon Rondo at 7. Not bad.

I then plugged in this years college draft individuals. I've attached the full results. Here are the top 10:
1. Anthony Davis
2. Jae Crowder
3. John Henson
4. Bradley Beal
5. Michael Kidd-Gilchrist
6. Jeremy Lamb
7. Will Barton
8. Damian Lillard
9. Jared Sullinger
10. Draymond Green

Some others of note:
30. Austin Rivers
36. Andre Drummond
40. Harrison Barnes

These results have a pretty good correlation with many mock drafts. But there are quite a few question marks in there that surprised me.

My favorites for the Blazers - Damian Lillard at 6, and either Sullinger or Zeller at 11. Let me know what you think.

WOW! Welcome to S2!

Hell of a first post! Look forward to reading more from you.

 

[42N8Bounce]

BdB is my initials. It also stands for Basketball data Base.

You're right. Grading the success of an NBA player is quite subjective. Doing it for over 500 players gets grueling. The basics -
100 = 5 + time All Star
90 = 2+ time all star
80 = all star 1 time
70 = high end starter 15 + points and or long successful career.
60 = average starter 10-15 points a game.
50 = low end starter 10- points a game.
40 = high end backup (started less than half their games played)
30 = average backup
20 = low end backup
10 = barely played in the NBA
0 = played less than a full season in the NBA

The challenge was determining how to weight the importance of each stat category. I primarily looked at the basic stats such as points, rebounds, assists, blocks, steals, fouls, turnovers, fg%, ft%, 3pt%, 3pt shot selection. I also added a factor for the player's height, so it is primarily looking for an individual similar in size. Equalized everything by per 40, added a class factor, and school factor. Whew. I then added filter criteria to eliminate deviations outside the norm (if it finds 5 similar player rated about 40-50, and one rated at a 10, it will throw out the 10). I also use a per game contribution factor similar to Hollinger's formula to compare per game contributions per 40. If it finds a statistically similar player, but their Hollinger per game number is greater than a certain factor, it throws that one out. Hope that helps clarify a bit. Sorry to bore with the details. I'm an engineer, so I enjoy the math side of this.

When I compared the program results to the GMs, I took the top 5/10/15 actual college players selected in the draft, and added up the players scores. I did the same for my program results. For example, If the GMs got a player rated 80, 70, 30, 90 and 40 with the top 5 picks (310 total), and this program grabbed player with scores 15, 40, 80, 90, 60 (285 total), then the GMs beat me by 25. 25/310 ~ 8%. I did this for 8 different draft years, and looked at 3 sections of each draft. I attached results summary pages if you are interested to see the players this program selected each year.

 

[42N8Bounce]

I've been reading this site for years. You guys are entertaining. Never had the urge to contribute until now. The fam and friends encouraged me to share these results. I figured you may enjoy it.

So much of what we do is based off of emotion. Rooting for particular schools, etc. It's interesting when you take the emotion (and the "potential" word) out of the equation and see what's left.

Personally I don't think Jae Crowder is the second best player in the draft. I also think TRob is better than the 15th rated player. Is Drummond really the 36th best player? I guess we'll see...

 

[jlprk]

Do any of the 500 players fit into McMillan's system?

 

[BrianFromWA]

Pretty good. I'm an engineer myself, so I get it.

Here's another wrench to toss in...can you (or do you need to?) put in a per-draft normalization factor? For instance, a GM should be penalized for taking Darko or Thabeet #2, when there were great players available. But if I'm reading this right (no guarantee at almost midnight) then you're counting this across the years, which means that you could be penalizing a GM for taking Bargnani #1 when in other years Melo was available at #3, which doesn't seem right.

 

[42N8Bounce]

Do any of the 500 players fit into McMillan's system?

Travis Outlaw. But he was a HS kid, so nope.

 

[Fez Hammersticks]

Can you give a more specific reason why Lillard ranks so high?

 

[THE HCP]

You need to now collect data on the posters of S2 and rank them.

 

[jlprk]

You need to now collect data on the posters of S2 and rank them.

This guy has the power to destroy you. For your own good, keep quiet.

 

[THE HCP]

Actually this might be the first rookie that intimidates The HCP............ with his NERDNESS.

 

[42N8Bounce]

Can you give a more specific reason why Lillard ranks so high?

I can tell you some of the matches the program found for Lillard - Jason Terry, Luther Head, Gilbert Arenas, and Juan Dixon are a few.

 

[42N8Bounce]

Actually this might be the first rookie that intimidates The HCP............ with his NERDNESS.

I have a few spare pocket protectors I'll share if that helps.

 

[Fez Hammersticks]

This program -- what were the matches for Westbrook and Rose?

 

[jlprk]

How does Crowder compare to Wesley Matthews? Other than being from Marquette.

 

[THE HCP]

I have a few spare pocket protectors I'll share if that helps.

Just messing with you man. Keep bringing the data.

 

[42N8Bounce]

This program -- what were the matches for Westbrook and Rose?

Westbrook it only ranked as the 14th best player that year. Matched with - Ramon Sessions, Moochie Norris, Keith Bogans, and Tyronn Lue.

Rose it grabbed at number 5. Matched with - Doug Christie, Kirk Hinrich, Jarrett Jack, and Jason Kidd.

 

[42N8Bounce]

How does Crowder compare to Wesley Matthews? Other than being from Marquette.

Jae Crowder is certainly the name that jumps out in that list. It found matches with - Ronnie Brewer, Doug Christie, Dan Majerle, and Scott Burrell.

 

[Fez Hammersticks]

Were you as high on Faried last year as many of us were?

 

[jlprk]

Actually this might be the first rookie that intimidates The HCP............ with his NERDNESS.

You stall for time while I probe his weaknesses.

 

[jlprk]

How does Barton compare to Rudy Fernandez?

 

[42N8Bounce]

Were you as on on Faried last year as many of us were?

Yep. I couldn't believe they went with Nolan Smith. Still can't believe it. I'm a believer in what the player actually produces. I don't care if he's short, skin color, fat, etc. I'm not a big believer in potential. If he's producing, get him. The knock on Faried was that he was too short. Hmm...

 

[42N8Bounce]

How does Barton compare to Rudy Fernandez?

Rudy doesn't have any college stats that the program can compare him to, but I can tell you some of the matches it found for Will Barton -
Michael Redd, Mike Miller, Shane Battier, and Thaddeus Young.