NINA

After six baseball seasons I am leaving the Statcast baseball data team at Major League Baseball. I’m enormously grateful to have had the opportunity to work at MLB, but it was time for a change and the pendulum to swing back to my roots of music and innovation. The big news is that I’ll be joining Nina Protocol as their first dedicated backend engineer, founded by Mike Pollard, Eric Farber, and Jack Callahan. We all share the strong fundamental belief that online music platforms and tools do not currently serve the needs of independent musicians and it’s only recently that decentralized blockchain technology is at a point where artists can take full control of their creative work knowing that it can survive past the lifetime of a centralized music platform. It’s very early days and the time to build is now.

For most of my adult life until I was in my mid-thirties, music and being involved in a community of experimental musicians dominated my time and energy. Always running in parallel was immersing myself in software engineering and learning as much as I could, and pretty much whatever supplemental income I had at my disposal was reinvested in music and putting out records for other people. This pretty much went on for years and I absolutely benefitted growing up in Oakland and the Bay Area at large which had an incredibly rich tapestry of electronic and experimental musician weirdos as well as an innovative hub of computer history in Silicon Valley. Eventually a wave of blandness enveloped San Francisco in the 2010’s dominated by bloated adtech, MBA’s leaving finance, and product managers that just took their Agile certification to get in on the wild carnival ride.

My first job coding was in the summer at age 15 and I never really looked back. Occasionally these worlds would intersect but for the most part I discovered over time that it was entirely healthy to not have my job depend on music and vice versa. In that time however, it became increasingly clear after many years that even amongst my most successful music peers, there really wasn’t much of an economy for releasing limited runs of vinyl that took years of effort for everyone involved only for it to be written and tweeted about for a month and then disposed of in an increasingly dystopian streaming platform world where power law curves dictated a winner take all business model. I cherished publishing an artifact that could sit on someone’s shelf for decades that could outlast most technology companies and loved labels that took this idea very seriously.

The universe has a way of slamming the door shut on an epoch of your life whether you’re ready for it or not, and that’s pretty much what happened with me at the end of 2016 and the first couple of months in 2017 that complicated my relationship with music. There were three key events that happened all within two months of each other. I had come off of a tour with legendary Coil collaborator Ivan Pavlov (COH) and had an unfortunate falling out with the label I was releasing music for. The Ghost Ship tragedy had just happened right around the same time which I’ve written about before, and it really ripped the soul out of the Bay Area experimental community and left a hole in our hearts collectively that will never go away. And lastly, I had resigned from the company I had worked for which had recently been acquired by a major streaming music company which I was pretty dejected about because it ran counter to my values as an independent musician and I was unwillingly sucked into it. Several months later I ceased operations with Isounderscore, the label I had started at age 23 ending a 12 year run. I still worked on music over the next five years but everything slowed down considerably to a grueling crawl with two releases to show for it. I focused more on rebalancing my priorities as a new dad and a large amount of focus on my next work opportunity.

When I was six years old, to help make sense of a world where the 1988 Dodgers took down my juggernaut Oakland Athletics in the World Series I had the idea to compile the statistics from the 1989 Fleer baseball set for each team for a first grade science project to demonstrate that the Athletics were in fact the superior team. Throughout the course of my life growing up I would voraciously consume advanced statistics and always did well in math, and was well aware of what Billy Beane and the Oakland Athletics were doing as a small online community of nerdy A’s fans before Moneyball became a thing. But ultimately, I really had no idea how far the rabbit hole went with baseball analytics and baseball data pipelines. A small subset of my music friends knew that I was really into this kind of thing.

That’s why jumping into one of my other passions which was baseball data and analytics was the perfect pivot, and really for the first time in my life I owed it to myself to do something completely different which is why I joined MLB Advanced Media back in 2017 before the Bamtech deal spun us off as a technology organization at MLB. Many people don’t realize this but it’s a very small team in San Francisco that helped build out the baseball data infrastructure for Statcast which involved heavy collaboration with the fine folks over in New York operating out of the MLB headquarters. My role was to work very closely on helping create real-time metrics and a lot of the backend engineering. I was totally obsessed with the Statcast data for years and it forever changed the way I think about and experience baseball. To see how that changed the game of baseball in a very short amount of time while having a small part in it first hand really blew me away.

I’m incredibly grateful for my time at MLB and the opportunity to meet people across the baseball industry. It’s humbling to have had the privilege to collaborate directly with people over the years like Tom Tango, Mike Petriello, a really talented group of analysts and data scientists like Jason Bernard and Travis Peterson, our physicist Clay Nunnally and of course the software engineering team in the San Francisco office that I was a part of behind the scenes doing a lot of heavy lifting. When I met Daren Willman for the first time when I came to Houston in 2017, he demonstrated what southern hospitality meant with his generosity and is now helping rebuild the Texas Rangers in his post Statcast career. Of course, I would be remiss if I didn’t mention that I am indebted to Rob Engel for giving me the opportunity to work at MLB, he is incredibly humble and the man behind the curtain since the very beginning of Statcast’s inception. The truth is that the biodiversity and expertise across multiple technological domains under Major League Baseball is impressive, and the scale that is required to support the game of baseball whether it’s on the field or behind the scenes is truly humbling.

For the first time in a very long time I’m actually looking forward to enjoying baseball simply as a fan again, even if it means braving the Astros crowd in my now dated kelly green Matt Olson jersey when the A’s come to Houston. I really don’t know if I’ll ever work in baseball again, who knows? I’ll probably make some public contributions here and there for the community with some rare downtime. But it’s time to take care of some unfinished business and help build the tools that I would have loved to have had in the 2000’s and 2010’s working on music and the label. I really could not have found a better place to do that at right now than at Nina.

Time to get to work.

SLOW XGBOOST ON APPLE M1

I recently purchased an Apple M1 Max with 64GB of RAM as the old 2016 Macbook is slowly dying with the battery giving out and the machine randomly restarting with anything processor intensive. I actually had to send the original M1 I purchased back to Apple after a few days due to a hardware manufacturing issue with the screen flickering. Once the new replacement finally came, one of the tasks at hand was migrating all of my code on the personal computer to the new one and setting up the development environment. It went pretty smoothly until I ran one of my NBA models and noticed that it ran excruciatingly slow. What gives? This computer is a beast but there was a significant performance hit with one of my models running in Python and this computer is light years ahead of the 2016 Macbook Pro so I dove into what was going on.

Here was the time output of the NBA model on the new Apple M1 Max:

python ./nba_model.py 20221022 2196.36s user 642.10s system 385% cpu 12:15.39 total

This ran roughly an order of magnitude slower on the new machine whereas on the old Macbook it would finish in about 2-3 minutes. Clearly something was wrong so I ran htop to see how things were running and after doing some research I began to suspect it was an issue running on Apple Silicon since these new M1 machines are using their own CPU and universal memory architecture instead of Intel’s. There were a lot of threads online but nothing specific about xgboost being slow on M1’s. After some fiddling around and experimentation I was able to figure out that this was a tale of two package managers. Initially I installed xgboost the “correct” Anaconda way:

(base) nickell@mlm1 % conda install xgboost
Collecting package metadata (current_repodata.json): done
Solving environment: done

Package Plan

environment location: /Users/nickell/opt/anaconda3

added / updated specs:
– xgboost

The following NEW packages will be INSTALLED:

_py-xgboost-mutex pkgs/main/osx-64::_py-xgboost-mutex-2.0-cpu_0 None
libxgboost pkgs/main/osx-64::libxgboost-1.5.0-he9d5cce_2 None
py-xgboost pkgs/main/osx-64::py-xgboost-1.5.0-py39hecd8cb5_2 None
xgboost pkgs/main/osx-64::xgboost-1.5.0-py39hecd8cb5_2 None

Proceed ([y]/n)? y

Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Retrieving notices: …working… done
(base) nickell@mlm1 pops %

After accepting that this library install was too slow, I proceeded with the uninstall. Now instead of using Anaconda, let’s try old school pip:

(base) nickell@mlm1 % pip install xgboost
Collecting xgboost
Downloading xgboost-1.6.2-py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64.whl (1.7 MB)
1.7/1.7 MB 13.0 MB/s eta 0:00:00

Lo and behold, here’s the improved performance time:

python ./nba_model.py 20221022 105.95s user 23.25s system 439% cpu 29.416 total

A performance improvement of 20x. The moral of the story is that if you’re installing xgboost on the new Apple M1 use pip install and not conda install. It would be a good exercise to build from source. My overall takeaway is to keep an eye on the performance of certain python libraries and packages on the M1 as it’s still a relatively new target architecture. Even running PyTorch on M1 GPU’s has only been around since May: https://pytorch.org/blog/introducing-accelerated-pytorch-training-on-mac/. If I run into similar issues with other packages then reinstalling with a different package manager is the first place I’d look.

NBA 2022-23 PREDICTIONS

Warriors preseason game against the Lakers, first game back at Chase as NBA champions.

Let’s get this out of the way first, I’ll probably get a bunch of these wrong but the model that’s been deployed has spoken and we’re going to roll with it for better or worse. If anything it will be fun to figure out what went wrong and how physical reality played out in the end. I’ve picked the Milwaukee Bucks as the team with the most wins and defeating the defending NBA champion Golden State Warriors in the NBA Finals. The general thesis out there is that there will be an unprecedented level of tanking due to the Victor Wembanyama sweepstakes which is valid, however I’m taking a much different angle because I think we’ll actually see a smoothing in the lower tier. We’ll see that it’s actually hard for more than 6-7 teams to all out-tank each other due to diminishing returns and ultimately there will be wins to be had at the bottom. My projection for the Mavericks is probably too low but I think this team is heavily overvalued and flat out bad, just ask the question who their second best player is behind Luka and then take a look at the cast supporting him. I think that Boston actually played a bit out of their shoes last year and are going to see a heavy regression. Two teams that I believe will take a big step forward this year will be the New Orleans Pelicans and New York Knicks, and we’ll see good playoff bound teams like the Phoenix Suns and LA Clippers start sliding while underperforming expectations.

TEAM RANKINGS

  1. Milwaukee Bucks (Over 52.5 wins)
  2. Brooklyn Nets (Under 50.5 wins)
  3. Philadelphia 76ers (Under 50.5 wins)
  4. Golden State Warriors (Under 51.5 wins)
  5. New Orleans Pelicans (Over 44.5 wins)
  6. Denver Nuggets (Under 49.5 wins)
  7. New York Knicks (Over 38.5 wins)
  8. Memphis Grizzlies (Under 48.5 wins)
  9. Los Angeles Clippers (Under 52.5 wins)
  10. Phoenix Suns (Under 52.5 wins)
  11. Cleveland Cavaliers (Under 47.5 wins)
  12. Los Angeles Lakers (Under 45.5 wins)
  13. Miami Heat (Under 48.5 wins)
  14. Boston Celtics (Under 53.5 wins)
  15. Portland Trailblazers (Over 39.5 wins)
  16. Atlanta Hawks (Under 45.5 wins)
  17. Toronto Raptors (Under 45.5 wins)
  18. Minnesota T-Wolves (Under 48.5 wins)
  19. Washington Wizards (Over 35.5 wins)
  20. Utah Jazz (Over 24.5 wins)
  21. Charlotte Hornets (Over 35.5 wins)
  22. Chicago Bulls (Under 41.5 wins)
  23. Orlando Magic (Over 26.5 wins)
  24. Indiana Pacers (Over 23.5 wins)
  25. San Antonio Spurs (Over 22.5 wins)
  26. Oklahoma City Thunder (Over 23.5 wins)
  27. Sacramento Kings (Under 33.5 wins)
  28. Detroit Pistons (Under 29.5 wins)
  29. Dallas Mavericks (Under 48.5 wins)
  30. Houston Rockets (Under 23.5 wins)

PLAYOFF SCENARIOS

Play-in West: Minnesota over Utah
Play-in East: Toronto over Washington

7th Seed West: Lakers over Portland
7th Seed East: Boston over Atlanta

8th Seed West: Minnesota over Portland
8th Seed East: Atlanta over Toronto

First Round West 1-8: Golden State over Minnesota
First Round East 1-8: Milwaukee over Atlanta

First Round West 2-7: New Orleans over Lakers
First Round East 2-7: Brooklyn over Boston

First Round West 3-6: Denver over Phoenix
First Round East 3-6: Philadelphia over Miami

First Round West 4-5: Clippers over Memphis
First Round East 4-5: Cleveland over New York

West Semifinals 1: Golden State over Clippers
West Semifinals 2: Denver over New Orleans

East Semifinals 1: Milwaukee over Cleveland
East Semifinals 2: Brooklyn over Philadelphia

Western Conference Finals: Golden State over Denver
Eastern Conference Finals: Milwaukee over Brooklyn

NBA Finals: Milwaukee over Golden State

WINNER OF THE WEMBANYAMA SWEEPSTAKES

Houston Rockets

ROOKIE OF THE YEAR

Paolo Banchero

MOST VALUABLE PLAYER

Giannis Antetokounmpo

DEFENSIVE PLAYER OF THE YEAR

Andrew Wiggins

LONE STAR

I ventured out to a show for the first time in over two years since the beginning of the pandemic and the first one since moving to the Houston area. The last show before this was days before the shutdown back in March 2020 curated by Michael Castaneda via Sunwarped, and as a non-participant it was attending Hive Mind in Oakland around January that same year which in itself had a long lapse. Needless to say this was long overdue and finding something like this was very cathartic.

The venue itself is legendary and built by postal worker Jefferson Davis McKissack between 1956 through 1979 and something of a folk-art landmark. After being more or less confounded stumbling into this place for the first time and finding the other stage, the sound was stellar from some familiar faces. An overwhelming feeling of never taking DIY shows and venues for granted again, and it was also a perfect way to help purge the darkness of Uvalde just 300 miles away and some other unfortunate relative circumstances that have come to light.

Outside the venue
Studded Left…Chuck from Better Call Saul would enjoy this band
In Spite of Dreams
Future Blondes

In other news currently working on another Nina release which is the platform of choice for the foreseeable future. The previous release Inverted Void is sold out. Without getting into the nauseating evangelization of Web3 or decentralized tech (that certainly warrants another post in itself), I’m fully convinced this is path forward for self-sustaining artists. I highly recommend checking them out, founded by peers I highly admire and respect. There will be more very soon…

I promise.

Ashley P. Svn (1985-2021)

I was passed along news that Ashley P. Svn unexpectedly passed away peacefully at home last Tuesday afternoon on August 17th, 2021 due to an ongoing illness that had been going on for some time. There aren’t many details right now.

For those that knew Ashley, it wasn’t a secret they had many demons to contend with, but like many talented and troubled artists that wrestle with the abyss they can emerge for brief periods and conjure up a creative energy that otherwise wouldn’t exist. Like many in our very small community, I had fallen out of touch with Ashley over the past three years. Fortunately in my case, I had the privilege of working with them during most of the good and very productive periods in between those troubling times of their life, and helped release their HOM “A$X” LP on my old record label Isounderscore, one of the last two records I released before ceasing operations in 2017. In an odd twist, the roommates that were with Ashley were looking for any contact information and found my friend Thomas Dimuzio’s name on the back of the “A$X” LP he mastered. They contacted him with the message and it was then that Thomas forwarded me the very tragic news.

HOM “A$X” LP released 2017 on Isounderscore. Ashley’s last released recordings.

I remember discovering Ashley’s solo work as HOM sometime around 2014 through my friend Michael Buchanan’s production and remix work on a HOM 12″ EP called “Bound / Somn” released through the Motor Collective based out of Seattle, Washington. Meanwhile, the Bay Area was going through a revival of weird techno and electronic music at the time for a variety of reasons that emerged out of a convergence of phenomena including the popularity of hardware and modular synthesis and an evolution of experimental musicians that worked in noise and non-rhythmic areas picking up drum machines and sequencers again. Naturally, another consequence of this as it is with any genre of music, there was an immediate oversaturation of techno which was a huge turn off to me. However, Ashley’s HOM project had unique and intangible qualities in the music.

As I would discover, they were part of a duo prior to the HOM project called “Thee Source ov Faunation” or an alias as “Thee Source” which appeared to have been influenced by early Psychic TV without the cringeworthy cliches and possessed a magical and mystical quality to the music. After discovering this work it was clear how it bridged into Ashley’s HOM project. After doing my research I directly sought out Ashley and contacted them to meet up. It turned out they were playing a show out in West Oakland and were in the middle of bouncing around between the Pacific Northwest and the Bay Area. We talked at length and struck up a friendship and had asked them if they were interested in doing an LP. From there on we had kept in touch, and I was largely unaware early on that they were going through some difficult times but they would later express that the project would help them significantly and allowed them to focus on their creative work. I never was able to track down physical copies of Thee Source, as they were released in tiny editions and the circulation was very tight. Thankfully some are still online.

Over the years there would be many phone calls out of the blue that were a bit surreal at times with where Ashley’s head would be at. I could tell they were struggling, but always enjoyed the conversations because we shared a common thread and goal of getting the work done and out there because ultimately I believed in the unique imprint of what they were doing. One story that stands out in my mind as I’m still processing everything as I write this is when Ashley revealed that their parents both passed away at a young age but emphasized that they provided them with an experience of growing up in a very creative and artistic household. That was a real gift, and they lived art and breathed it in extreme ways. I had recently become a father for the first time, and they stressed the importance of being there as a father for my little girl and I understood where that came from.

The reality is that our world is smaller than we think it is. I was telling a friend Sunday night who also knew Ashley that the past five years with losing friends in the Ghost Ship tragedy, society ripping itself apart on social media, and a global pandemic has accelerated an isolation and disconnectedness that’s more real than ever. The experimental music community is very small, and those of us that have gone through what we’ve been through have a lingering black pool deeply seated in our unconscious that unfortunately is never going to go away. I never talked about the Ghost Ship tragedy publicly and losing our friends like Barrett Clark. For months I would wake up in the middle of the night with the same nightmare–no sound, black smoke filling a room rapidly, and then waking up. Ashley and I would share stories and anecdotes about the people we lost in that tragedy, and their passing last Tuesday was a complete trigger of that black cloud filling the room. Even with starting a family, working as an engineer in baseball, and moving to Houston Texas during the middle of pandemic, I still feel connected to all of this years later that’s very difficult to articulate to normal people who are outsiders.

Ashley was a very shadowy figure even by experimental music standards, but was very well connected in the underground experimental music scene across the West Coast. I really hope that the people that knew them can celebrate their work in a way I wish I could have done when I was still running the Isounderscore label.

Rest in Peace.

NBA Projections • Tue 07/20/21

Resulting Model Score: 90.9%

player_idteamoppposnamesalaryvaluefpts
1073MILPHOPG/SGJrue Holiday9600-0.547.50
409301PHOMILCDeandre Ayton8200-2.838.25
1087PHOMILPGChris Paul9000-4.041.00
1498MILPHOCBrook Lopez5600-4.523.50
1005MILPHOPGJeff Teague2000-4.55.50
16852MILPHOPF/CGiannis Antetokounmpo12800-4.559.50
13990MILPHOSG/SFKhris Middleton10200-4.846.25
1115625PHOMILSF/PFCameron Johnson4400-5.017.00
13947MILPHOSF/PFP.J. Tucker3400-5.311.75
18941PHOMILPGCameron Payne4000-5.514.50
18920PHOMILCFrank Kaminsky1400-5.51.50
18939MILPHOSG/SFPat Connaughton5200-5.820.25
37861PHOMILSG/SFTorrey Craig2600-6.07.00
35179PHOMILSF/PFAbdel Nader1600-7.30.75
18909MILPHOPF/CBobby Portis5000-7.817.25
36052MILPHOPG/SGBryn Forbes1800-8.50.50
13942PHOMILSF/PFJae Crowder7400-9.527.50
18949PHOMILSGDevin Booker10400-10.341.75
408842PHOMILSFMikal Bridges6600-13.319.75

NBA Projections • Sat 07/17/21

Resulting Model Score: 93.1%

player_idteamoppposnamesalaryvaluefpts
409301PHOMILCDeandre Ayton80001.039.62
1115625PHOMILSF/PFCameron Johnson4000-0.818.53
16852MILPHOPF/CGiannis Antetokounmpo12600-2.859.82
1005MILPHOPGJeff Teague1800-3.36.66
37861PHOMILSG/SFTorrey Craig2400-4.010.51
1087PHOMILPGChris Paul8800-4.542.30
1073MILPHOPG/SGJrue Holiday9600-4.541.75
35179PHOMILSF/PFAbdel Nader1200-5.30.75
18939MILPHOSG/SFPat Connaughton4800-5.517.89
18920PHOMILCFrank Kaminsky1400-5.51.35
13947MILPHOSF/PFP.J. Tucker3600-6.311.98
36052MILPHOPG/SGBryn Forbes1600-6.51.54
13990MILPHOSG/SFKhris Middleton10400-7.344.37
18941PHOMILPGCameron Payne4400-9.014.79
1498MILPHOCBrook Lopez6000-10.518.12
13942PHOMILSF/PFJae Crowder7400-11.026.68
18909MILPHOPF/CBobby Portis5600-12.317.27
18949PHOMILSGDevin Booker10200-12.543.13
408842PHOMILSFMikal Bridges6800-15.320.70

NBA Projections • Wed 07/14/21

Resulting Model Score: 89.7%

player_idteamoppposnamesalaryvaluefpts
409301PHOMILCDeandre Ayton84000.542.50
1115625PHOMILSF/PFCameron Johnson3800-1.317.75
16852MILPHOPF/CGiannis Antetokounmpo12200-2.558.50
37861PHOMILSG/SFTorrey Craig1800-3.06.00
13947MILPHOSF/PFP.J. Tucker3400-3.014.00
1087PHOMILPGChris Paul9600-3.344.75
1073MILPHOPG/SGJrue Holiday9200-3.842.25
1005MILPHOPGJeff Teague2200-4.07.00
18939MILPHOSG/SFPat Connaughton4200-4.316.75
13990MILPHOSG/SFKhris Middleton10000-5.344.75
35179PHOMILSF/PFAbdel Nader1200-5.30.75
18920PHOMILCFrank Kaminsky2000-5.54.50
1498MILPHOCBrook Lopez6200-8.023.00
18941PHOMILPGCameron Payne4600-9.313.75
36052MILPHOPG/SGBryn Forbes2400-9.32.75
13942PHOMILSF/PFJae Crowder6800-11.522.50
18909MILPHOPF/CBobby Portis5400-13.513.50
18949PHOMILSGDevin Booker10400-15.836.25
408842PHOMILSFMikal Bridges7600-15.822.25

NBA Projections • Sun 07/11/21

Resulting Model Score: 83.7%

player_idteamoppposnamesalaryvaluefpts
37861PHOMILSG/SFTorrey Craig10001.56.50
1005MILPHOPGJeff Teague1800-1.37.75
18939MILPHOSG/SFPat Connaughton3800-1.517.50
409301PHOMILCDeandre Ayton9000-2.043.00
13990MILPHOSG/SFKhris Middleton9600-2.545.50
1087PHOMILPGChris Paul9800-2.546.50
1073MILPHOPG/SGJrue Holiday8800-3.540.50
35179PHOMILSF/PFAbdel Nader1000-3.81.25
18920PHOMILCFrank Kaminsky1600-4.33.75
16852MILPHOPF/CGiannis Antetokounmpo11800-5.553.50
1115625PHOMILSF/PFCameron Johnson4600-6.516.50
13947MILPHOSF/PFP.J. Tucker4200-6.514.50
1498MILPHOCBrook Lopez6600-7.825.25
36052MILPHOPG/SGBryn Forbes2600-8.84.25
13942PHOMILSF/PFJae Crowder6000-9.820.25
18941PHOMILPGCameron Payne4800-10.014.00
408842PHOMILSFMikal Bridges7200-13.522.50
18949PHOMILSGDevin Booker10600-15.837.25
18909MILPHOPF/CBobby Portis5200-17.38.75

NBA Projections • Thu 07/08/21

Resulting Model Score: 87.1%

player_idteamoppposnamesalaryvaluefpts
1073MILPHOPG/SGJrue Holiday88005.049.00
13990MILPHOSG/SFKhris Middleton98001.050.00
1005MILPHOPGJeff Teague14000.87.75
18909MILPHOPF/CBobby Portis32000.516.50
18920PHOMILCFrank Kaminsky10000.55.50
18941PHOMILPGCameron Payne38000.019.00
37861PHOMILSG/SFTorrey Craig2400-1.810.25
36052MILPHOPG/SGBryn Forbes1800-2.07.00
409301PHOMILCDeandre Ayton9200-2.543.50
1087PHOMILPGChris Paul10400-3.049.00
16852MILPHOPF/CGiannis Antetokounmpo11400-3.553.50
18939MILPHOSG/SFPat Connaughton4000-4.315.75
13947MILPHOSF/PFP.J. Tucker4600-7.315.75
13942PHOMILSF/PFJae Crowder5600-8.819.25
18949PHOMILSGDevin Booker10000-9.041.00
1115625PHOMILSF/PFCameron Johnson6000-11.818.25
1498MILPHOCBrook Lopez7600-13.025.00
408842PHOMILSFMikal Bridges6800-14.519.50
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