My data-driven draft predictions
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My data-driven draft predictions
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My data-driven draft predictions
I did some analysis on 30 years of lottery picks and 30 years of first round picks for the teams in this years lottery, and developed these predictions:
1 Cleveland Cavaliers
Typically target low raw scorers with little experience, alternating between 1-2 1st round Wings, then a Big
Nerlens Noel, Kentucky
0.25 ASTOCKS per minute (1 assist, steal or block every 4 minutes) exceeds all other Bigs
2 Orlando Magic
Draft a Wing once every 3 years AND every 11 years that can score (500+ points) and board (200+)
Otto Porter, Georgetown
Porter edges Oladipo in points and boards (in 5 fewer games), as well as being a more proficient three-point shooter
3 Washington Wizards
Typically pick durable (1000+ mins), scoring (0.5 pts per min) theives (3 steals per 40 min) at the Wing
Victor Oladipo, Indiana
The local product (DeMatha High School) more than fits the bill (1021 minutes, 0.48 pts per min, 3 thefts per 40 min)
4 Charlotte Bobcats
Positions drafted in 3-year cycles, with a high-scoring, shot-blocking Big from an “elite” (especially ACC/SEC) college up next
Alex Len, Maryland
Len is the biggest (7’1″), meanest (3 blocks per 40 min) scorer (0.45 pts per min) from the South (Maryland)
5 Phoenix Suns
Target non-college prospects at an above-average rate, and look for Wings that are durable (1100+ mins) and high-scoring (600+ pts), without much concern for per minute ASTOCKS
Glen Rice Jr., Rio Grande Valley (D-League)
The All-Star’s son has the scoring (696 pts, 0.57 per min), durability (1228 minutes) and experience (NBA D-League)
6 New Orleans Pelicans
Draft a Point Guard once every 3-6 years from an “elite” college that scores, steals and blocks at above-average lottery levels
Trey Burke, Michigan
No one in the Draft does it all better (0.53 pts per min, 1.8 thefts and 0.58 blocks per 40 min) than the National Player of the Year
7 Sacramento Kings
Historically draft a Point Guard every 7 years AND every 10 years, and value ASTOCKS in Point Guards (300+) more than scoring
Michael Carter-Williams, Syracuse
Carter-Williams scores at low per minute rate (0.34 pts per min), but is easily leads all PGs in the draft in ASTOCKS (0.3 per minute; 199 rebounds, 109 thefts, 291 assists)
8 Detroit Pistons
Target an “elite” school Wing every 2-4 years that can score (600+ pts, 0.48 per min) and dish (100+ assists), regardless of rebounding and thefts
Ben McLemore, Kansas
McLemore (589 pts, .49 per min, 73 assists) barely edges Crabbe on 3pt shooting and big-school recognition (Kansas over Cal)
9 Minnesota Timberwolves
Over the past 10 years a durable (950+ mins), scoring (500+ pts), rebounding (180+ boards) Wing gets picked once every 1-2 years
Allen Crabbe, California
Crabbe (1195 mins, 607 pts, 200 boards) is the best available, while still maintaining average passing and thefts (87 and 37, respectively)
10 Portland Trailblazers
Draft by position in in sprees over time (same position, consecutive years since 2002); expect a Big with HUSTLE (boards, thefts, assists, blocks)
Gorgui Dieng, Louisville
After Noel, no one is better per minute than the National Champ Dieng (310 rebounds, 44 thefts, 66 assists, 83 blocks; 0.19 ASTOCKS per min)
11 Philadelphia 76ers
Usually draft a Big that can score (500+ pts), board (average 290 rebounds) and swat (average 75 blocks) from non-”elite” colleges every 2-3 years
Mike Muscala, Bucknell
The Bucknell Bison (637 pts, 378 boards, 80 blocks) is a perfect fit
12 Oklahoma City Thunder
Select every 2-4 years a Big from a non-”elite” college that scores (500+ pts) and boards (250+ rebounds)
Anthony Bennett, UNLV
Bennett (UNLV, 564 pts, 285 rebounds) is the highest matching per-minute scorer (0.59 pts per min)
13 Dallas Mavericks
Historically have sprees of drafting Bigs in consecutive years, targeting theives (0.5+ steals per 40 min), rebounders (0.2-0.4 boards per min) and scorers (0.45-0.68 pts per min) from “elite” colleges
Mason Plumlee, Duke
Plumlee has the pedigree (Duke) and the stats (1.15 thefts per 40 min, 0.29 rebounds per min, 0.49 pts per min) that match
14 Utah Jazz
Usually draft well-rounded, small school Wings (500-600 pts, 200 boards, 40-50 thefts, 60-90 assists) on an alternating 1-year/2-3-year/1-year interval
Kentavious Caldwell-Pope, Georgia
Georgia Bulldog KCP is their ideal pick (591 points, 226 boards, 65 thefts, 58 assists)
I realize my picks are different than most mocks, curious to hear any feedback. Any questions on my methodology I can point you to a full description.
hoop_nerd
"less wrong...intelligently"
1 Cleveland Cavaliers
Typically target low raw scorers with little experience, alternating between 1-2 1st round Wings, then a Big
Nerlens Noel, Kentucky
0.25 ASTOCKS per minute (1 assist, steal or block every 4 minutes) exceeds all other Bigs
2 Orlando Magic
Draft a Wing once every 3 years AND every 11 years that can score (500+ points) and board (200+)
Otto Porter, Georgetown
Porter edges Oladipo in points and boards (in 5 fewer games), as well as being a more proficient three-point shooter
3 Washington Wizards
Typically pick durable (1000+ mins), scoring (0.5 pts per min) theives (3 steals per 40 min) at the Wing
Victor Oladipo, Indiana
The local product (DeMatha High School) more than fits the bill (1021 minutes, 0.48 pts per min, 3 thefts per 40 min)
4 Charlotte Bobcats
Positions drafted in 3-year cycles, with a high-scoring, shot-blocking Big from an “elite” (especially ACC/SEC) college up next
Alex Len, Maryland
Len is the biggest (7’1″), meanest (3 blocks per 40 min) scorer (0.45 pts per min) from the South (Maryland)
5 Phoenix Suns
Target non-college prospects at an above-average rate, and look for Wings that are durable (1100+ mins) and high-scoring (600+ pts), without much concern for per minute ASTOCKS
Glen Rice Jr., Rio Grande Valley (D-League)
The All-Star’s son has the scoring (696 pts, 0.57 per min), durability (1228 minutes) and experience (NBA D-League)
6 New Orleans Pelicans
Draft a Point Guard once every 3-6 years from an “elite” college that scores, steals and blocks at above-average lottery levels
Trey Burke, Michigan
No one in the Draft does it all better (0.53 pts per min, 1.8 thefts and 0.58 blocks per 40 min) than the National Player of the Year
7 Sacramento Kings
Historically draft a Point Guard every 7 years AND every 10 years, and value ASTOCKS in Point Guards (300+) more than scoring
Michael Carter-Williams, Syracuse
Carter-Williams scores at low per minute rate (0.34 pts per min), but is easily leads all PGs in the draft in ASTOCKS (0.3 per minute; 199 rebounds, 109 thefts, 291 assists)
8 Detroit Pistons
Target an “elite” school Wing every 2-4 years that can score (600+ pts, 0.48 per min) and dish (100+ assists), regardless of rebounding and thefts
Ben McLemore, Kansas
McLemore (589 pts, .49 per min, 73 assists) barely edges Crabbe on 3pt shooting and big-school recognition (Kansas over Cal)
9 Minnesota Timberwolves
Over the past 10 years a durable (950+ mins), scoring (500+ pts), rebounding (180+ boards) Wing gets picked once every 1-2 years
Allen Crabbe, California
Crabbe (1195 mins, 607 pts, 200 boards) is the best available, while still maintaining average passing and thefts (87 and 37, respectively)
10 Portland Trailblazers
Draft by position in in sprees over time (same position, consecutive years since 2002); expect a Big with HUSTLE (boards, thefts, assists, blocks)
Gorgui Dieng, Louisville
After Noel, no one is better per minute than the National Champ Dieng (310 rebounds, 44 thefts, 66 assists, 83 blocks; 0.19 ASTOCKS per min)
11 Philadelphia 76ers
Usually draft a Big that can score (500+ pts), board (average 290 rebounds) and swat (average 75 blocks) from non-”elite” colleges every 2-3 years
Mike Muscala, Bucknell
The Bucknell Bison (637 pts, 378 boards, 80 blocks) is a perfect fit
12 Oklahoma City Thunder
Select every 2-4 years a Big from a non-”elite” college that scores (500+ pts) and boards (250+ rebounds)
Anthony Bennett, UNLV
Bennett (UNLV, 564 pts, 285 rebounds) is the highest matching per-minute scorer (0.59 pts per min)
13 Dallas Mavericks
Historically have sprees of drafting Bigs in consecutive years, targeting theives (0.5+ steals per 40 min), rebounders (0.2-0.4 boards per min) and scorers (0.45-0.68 pts per min) from “elite” colleges
Mason Plumlee, Duke
Plumlee has the pedigree (Duke) and the stats (1.15 thefts per 40 min, 0.29 rebounds per min, 0.49 pts per min) that match
14 Utah Jazz
Usually draft well-rounded, small school Wings (500-600 pts, 200 boards, 40-50 thefts, 60-90 assists) on an alternating 1-year/2-3-year/1-year interval
Kentavious Caldwell-Pope, Georgia
Georgia Bulldog KCP is their ideal pick (591 points, 226 boards, 65 thefts, 58 assists)
I realize my picks are different than most mocks, curious to hear any feedback. Any questions on my methodology I can point you to a full description.
hoop_nerd
"less wrong...intelligently"
Re: My data-driven draft predictions
- djthesonicsfan
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Re: My data-driven draft predictions
Super happy we get Bennett! Thanks!
notSonics 2016
Starters - Trey, Roberson, KD, Ibaka, Adams
Rotation - Payne, Waiters, Green, McGary, Kanter
Bench - Collison, Christon, Brodgon, Huestis
Stash - Johnson, Abrine
Cut - Morrow
Trade - Singler
Draft - Brogdon
FA - Green
Starters - Trey, Roberson, KD, Ibaka, Adams
Rotation - Payne, Waiters, Green, McGary, Kanter
Bench - Collison, Christon, Brodgon, Huestis
Stash - Johnson, Abrine
Cut - Morrow
Trade - Singler
Draft - Brogdon
FA - Green
Re: My data-driven draft predictions
- Cammo101
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Re: My data-driven draft predictions
The major flaws here is you are not taking positional need into account and most of the decisions you are basing your pick on were made by people who are long gone.
At the end of the day, what these results prove is that you can't use raw data to make these kinds of decisions. If a computer tells you to draft Mike Muscala ahead of Anthony Bennett, you stop using the computer.
At the end of the day, what these results prove is that you can't use raw data to make these kinds of decisions. If a computer tells you to draft Mike Muscala ahead of Anthony Bennett, you stop using the computer.

Re: My data-driven draft predictions
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- Ballboy
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Re: My data-driven draft predictions
Good points...
Despite the changeover in management and decision-makers within a single organization over time, I was surprised to see how patterned and relatively predictable some of the picks are over time. Specific teams continually value specific skills in a player again and again over time.
So I did try to account for position/current team needs as much as possible. I looked at All-Star level players on a current roster when comparing what the team's patterns for picks have been (for example, Cleveland was trending toward picking a Point Guard or a Big, since they have an All-Star in Kyrie, it became obvious they would draft a Big). However, I wanted to remain as objective as possible; realistically these are lottery teams (minus OKC) and they need help across the board to simply win more games.
Further, my method is designed to ignore my personal opinion as much as possible. I don't like my Mike Muscala pick either, but if I just changed it because it didn't "look right" to me, I can't justify that method as sustainable and able to be replicated.
I don't think I will get all of these right, this time, but I think it is possible with this type of approach. Instead of throwing out the computer, I would rather get a different one; refining the analysis based on the most relevant data.
I appreciate the feedback!
hoop_nerd
"less wrong...intelligently"
Despite the changeover in management and decision-makers within a single organization over time, I was surprised to see how patterned and relatively predictable some of the picks are over time. Specific teams continually value specific skills in a player again and again over time.
So I did try to account for position/current team needs as much as possible. I looked at All-Star level players on a current roster when comparing what the team's patterns for picks have been (for example, Cleveland was trending toward picking a Point Guard or a Big, since they have an All-Star in Kyrie, it became obvious they would draft a Big). However, I wanted to remain as objective as possible; realistically these are lottery teams (minus OKC) and they need help across the board to simply win more games.
Further, my method is designed to ignore my personal opinion as much as possible. I don't like my Mike Muscala pick either, but if I just changed it because it didn't "look right" to me, I can't justify that method as sustainable and able to be replicated.
I don't think I will get all of these right, this time, but I think it is possible with this type of approach. Instead of throwing out the computer, I would rather get a different one; refining the analysis based on the most relevant data.
I appreciate the feedback!
hoop_nerd
"less wrong...intelligently"
Re: My data-driven draft predictions
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Re: My data-driven draft predictions
I love your mock draft! Your analysis is very interesting. I'll check back in after the draft to see how many hits your method was able to predict.
Easily the most fun of all the mock drafts I've read.
Easily the most fun of all the mock drafts I've read.
Re: My data-driven draft predictions
- Cammo101
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Re: My data-driven draft predictions
I think it is a very interesting approach, and it is cool to see where something like this gives you a crazy out of left field result.
Re: My data-driven draft predictions
- RunSunRun
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Re: My data-driven draft predictions
There may be rioting in Phoenix if we picked a guy projected to be a very late first / early second rounder with the #5 pick, unless $arver is trying to channel his inner Al Davis, 

Re: My data-driven draft predictions
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Re: My data-driven draft predictions
ImHeisenberg wrote:I love your mock draft! Your analysis is very interesting. I'll check back in after the draft to see how many hits your method was able to predict.
Easily the most fun of all the mock drafts I've read.
Thanks for the feedback, appreciate it... That is exactly what I plan on doing after Thursday night, comparing what I got right, and more importantly which ones were wrong... I will probably post a complete comparison through my main site
hoop_nerd
"less wrong...intelligently"
Re: My data-driven draft predictions
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Re: My data-driven draft predictions
RunSunRun wrote:There may be rioting in Phoenix if we picked a guy projected to be a very late first / early second rounder with the #5 pick, unless $arver is trying to channel his inner Al Davis,
So true, although isn't it entirely possible that $arver (well played, by the way) is in fact Al Davis 2.0?
hoop_nerd
"less wrong...intelligently"
Re: My data-driven draft predictions
- kmatrixg
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Re: My data-driven draft predictions
Cammo101 wrote:The major flaws here is you are not taking positional need into account and most of the decisions you are basing your pick on were made by people who are long gone.
At the end of the day, what these results prove is that you can't use raw data to make these kinds of decisions. If a computer tells you to draft Mike Muscala ahead of Anthony Bennett, you stop using the computer.
I was going to say, good resource, but absolutely no team need taken into account makes this a flawed attempt. Oladipo to a team that already has Beal and Wall? No way they waste the 3rd overall pick on a player who will undoubtedly be stuck on the bench until a trade happens. Bennett or Porter will go third.
Re: My data-driven draft predictions
- SlowPaced
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Re: My data-driven draft predictions
Sorry but no. So many picks are way off. Glen Rice Jr. with 5th? Come on.
Re: My data-driven draft predictions
- BigSlam
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Re: My data-driven draft predictions
This is by far the most thought out and interesting mock I have ever seen. Kudos to you hoop_nerd.
I'd be interested to see examples of players the teams have drafted in the past that fit the criteria - and how they worked out as NBA players.
Really good stuff though. Well done and thank you for putting in so much well thought out work.
I'd be interested to see examples of players the teams have drafted in the past that fit the criteria - and how they worked out as NBA players.
Really good stuff though. Well done and thank you for putting in so much well thought out work.
B B M F 'ers
Re: My data-driven draft predictions
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Re: My data-driven draft predictions
BigSlam wrote:This is by far the most thought out and interesting mock I have ever seen. Kudos to you hoop_nerd.
I'd be interested to see examples of players the teams have drafted in the past that fit the criteria - and how they worked out as NBA players.
Really good stuff though. Well done and thank you for putting in so much well thought out work.
Appreciate the feedback, many thanks... The real test will be how it performs on Thursday night.
Off the top of my head, the easiest comparisons are ones like the Pelicans, and the Chris Paul/Baron Davis/Trey Burke correlations, or the Joe Dumars/Allan Houston/Ben McLemore patterns for the Pistons, among many others.
Re: My data-driven draft predictions
- kmatrixg
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Re: My data-driven draft predictions
hoop_nerd wrote:BigSlam wrote:This is by far the most thought out and interesting mock I have ever seen. Kudos to you hoop_nerd.
I'd be interested to see examples of players the teams have drafted in the past that fit the criteria - and how they worked out as NBA players.
Really good stuff though. Well done and thank you for putting in so much well thought out work.
Appreciate the feedback, many thanks... The real test will be how it performs on Thursday night.
Off the top of my head, the easiest comparisons are ones like the Pelicans, and the Chris Paul/Baron Davis/Trey Burke correlations, or the Joe Dumars/Allan Houston/Ben McLemore patterns for the Pistons, among many others.
I was callous not to have given you a few positives in your mock - such as picks:
2. Otto Porter
4. Alex Len
6. Trey Burke
7 MCW
13 Plumlee
14 Caldwell-Pope
The way these picks were generated are interesting, and well within reason. However, guys like Muscala (who very well may go 16-24) are simply placed too high. Rice Jr is looking at the same projection simply because players of this mold (Faried, Lawson for example) aren't projected to have as high of potential as other guys in the draft. The simple rule of thumb is draft for potential through the lottery and mid-first. After that, it's all players who you will give you what you expect, and nothing more.
Re: My data-driven draft predictions
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Re: My data-driven draft predictions
kmatrixg wrote:hoop_nerd wrote:BigSlam wrote:This is by far the most thought out and interesting mock I have ever seen. Kudos to you hoop_nerd.
I'd be interested to see examples of players the teams have drafted in the past that fit the criteria - and how they worked out as NBA players.
Really good stuff though. Well done and thank you for putting in so much well thought out work.
Appreciate the feedback, many thanks... The real test will be how it performs on Thursday night.
Off the top of my head, the easiest comparisons are ones like the Pelicans, and the Chris Paul/Baron Davis/Trey Burke correlations, or the Joe Dumars/Allan Houston/Ben McLemore patterns for the Pistons, among many others.
I was callous not to have given you a few positives in your mock - such as picks:
2. Otto Porter
4. Alex Len
6. Trey Burke
7 MCW
13 Plumlee
14 Caldwell-Pope
The way these picks were generated are interesting, and well within reason. However, guys like Muscala (who very well may go 16-24) are simply placed too high. Rice Jr is looking at the same projection simply because players of this mold (Faried, Lawson for example) aren't projected to have as high of potential as other guys in the draft. The simple rule of thumb is draft for potential through the lottery and mid-first. After that, it's all players who you will give you what you expect, and nothing more.
Thanks for the feedback.... Those few positives are almost 50% of the lottery - works for me.
Agreed on Muscala and Rice Jr, those two + Crabbe to the T-Wolves have me the most curious.
I'm actually most interested in seeing which ones I get wrong and figuring out why. It will be easy to explain if its a similar player, just valued higher (ie Zeller or Olynyk over Muscala) - in that case the process works, just needs refining.
Re: My data-driven draft predictions
- babyjax13
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Re: My data-driven draft predictions
McCollum seems to fit the mold you have outlined for the Jazz as well.

JazzMatt13 wrote:just because I think aliens probably have to do with JFK, doesn't mean my theory that Jazz will never get Wiggins, isn't true.
JColl
Re: My data-driven draft predictions
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Re: My data-driven draft predictions
I definitely don't understand the logic of the Cavs taking a big (using your analytics). Could much more easily justify a wing especially since they took a big each of the last 2 years.
UncleDrew wrote: I get Buckets!
Re: My data-driven draft predictions
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Re: My data-driven draft predictions
babyjax13 wrote:McCollum seems to fit the mold you have outlined for the Jazz as well.
Yes exactly... I had McCollum as a second or third option at this pick. Really KCP, Crabbe and McCollum ranked at pretty similar levels; I could see some combination of 2 of them going to the T-wolves and Jazz.
Re: My data-driven draft predictions
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Re: My data-driven draft predictions
TheOUTLAW wrote:I definitely don't understand the logic of the Cavs taking a big (using your analytics). Could much more easily justify a wing especially since they took a big each of the last 2 years.
It's really a combination of factors.... Specifically in this case, something like 24 of the #1 picks in the past 30 years have been a Big; not entirely a smoking gun, but definitely indicates the preference for picking Bigs (the easy counter to that is that 2 of non-bigs at #1 were picked by the Cavs).
But then it's also about patterns among the teams draft behavior - the frequency, intervals between, and significant stats a team values at a position. The Cavs usually rotate between a Wing and Big/Point Guard. Off the top of my head I don't think they've ever drafted three straight Wings, they rotate.
Further, the Cavs have shown a general apathy towards college experience... So in some ways, even at a different position, Noel is more like James and Irving than we realize (in terms of experience).
I hope this clarifies, happy to discuss further.