Applying March Madness Neural Networks to the NBA Bubble Restart
Those of you who have been following this blog for a while know about my March Madness neural network MadNet and the complimentary “bet sizing” neural network MetaNet. Unfortunately, I wasn’t able to put these neural networks to use this year since the college basketball March Madness tournament was cancelled due to the CovId pandemic. But with the NBA restart on the horizon, I decided to try applying these neural networks to the first few games of the NBA season restart in the Orlando “bubble”.
Unlike the March Madness neural networks, which use a “Wins Above Seeding” metric to determine how well a team would perform, for the NBA season restart I used a Python script to scrape data from Sports Reference on how well a team performs during the first 4 games of the season. This “First Games Won”, or FGW, would serve as a good proxy for how well a given team performs after an extended break (like the one the NBA just experienced). Given the awkward linear way these game results are listed on Sports Reference, it took a tricky bit of hash table magic in Python to scrape this data. Next, I scraped data related to each team’s season average Three Point Percentage, Two Point Percentage, and Rebounds /Assists /Steals / Blocks /Turnovers / Points per 100 minutes of play. The idea here is that teams with certain “profiles” perform better at the start of a season, after an extended break. I trained the neural network on this data to predict the FGW score of each team in the current season based on the stats that make up the team’s “profile”. My dataset included every NBA team from the 2012–2013 season to the 2018–2019 season (ignoring the lockout shortened 2011–2012 season that might have skewed the data, as well as all seasons prior to it).
I then scraped the same data for the 2020 season, and used both MadNet and MetaNet to predict each team’s performance. Since there were no trades from the time the NBA shut down in March to now, I expect most teams to maintain the same general “profile” at this time (with the exception of injuries and players who have chosen to sit out). Given the smaller dataset, I played with the number of hidden layers in both models, and was able to use fewer nodes while getting good results.
I trained 10 MadNet neural networks and 10 MetaNet neural networks each, and averaged the results. MadNet particularly liked the Spurs, giving them a FGW score of 4, followed by the Lakers, Celtics, Pelicans (who now have Zion Williamson joining a team that’s already expected to do well after a long break), and Magic (who may already have some homecourt advantage given how they don’t need to adjust to the humidity in Orlando). MadNet also disliked the Raptors (a top team that may be in for a rough restart), Wizards (who are already depleted without Bradley Beal), Grizzlies, and Bucks (another top team that may be in for a rough restart, especially since their first game back will be against the high FGW Celtics, and their starting point guard and third best player Eric Bledsoe has only recently recovered from Coronavirus).
Meanwhile, MetaNet also liked the Spurs the most, followed by the Rockets, Mavs, Lakers and Suns. With both MetaNet and MadNet signaling that the Spurs could have a great restart, it’s a real shame that their star player LaMarcus Aldridge is out for the season — otherwise they would have made for a great underrated bet! MetaNet didn’t like the Nets (who have already been decimated to the point of offering minutes to 40 year old Jamal Crawford!), Raptors (there they are in the poor restarting teams list again!), Bucks (also showing up among the poor restart teams again!), and Wizards.
After using an algorithmic approach to combine the results from MadNet and MetaNet, and adding in an adjustment factor based on which players are missing and the Vegas odds, here are my picks for the first two days of games after the restart (note that I’m not recommending you gamble here, nor am I qualified to give any advice — I’m simply pointing out what the data indicates when taken in conjunction with bookmaker odds):
Pelicans (-130) over Jazz — Both MadNet and MetaNet really like the Pelicans — and that’s BEFORE accounting for the force of nature that is Zion Williamson. Meanwhile, the Jazz will be missing their best perimeter threat, Bojan Bogdanovic.
Celtics (+170) over Bucks — Both MadNet and MetaNet felt the Bucks would have a slow start, plus Eric Bledsoe might be feeling the effects of his recent bout with CovId. Meanwhile, Boston has their full roster showing up in Orlando. I would actually go big on both the moneyline and the spread (Boston +5.0) in this one.
Magic (-230) over Nets — Vegas has a huge hold on this game, but the data favors the Magic in every conceivable dimension, and the Nets are beyond shorthanded at this point. This feels a bit like betting on Floyd Mayweather in his fight with Conor MacGregor — easy but boring.
Suns (N/A) over Wizards— MetaNet likes the Suns and absolutely hates the Wizards. That being said, the moneyline on the Suns (-290) is so skewed that my algorithm doesn’t recommend this one — even though it’s convinced the Suns will win.
Spurs (+130) over Kings — MadNet and MetaNet both love the Spurs teams’ profile more than any other, but major caveat, that’s with mid-range maestro LaMarcus Aldridge on the roster. Even with LaMarcus gone though, this is still a Spurs team that: 1) the data REALLY likes (2x more than it likes any other team), 2) is coached by the brilliant and always on top of things Greg Popovich, and 3) is going up against a young Kings team with 4 players who recently tested positive for CovId. Definitely worth taking a chance on the Spurs in this one — and they may even be worth a bet on the spread!
Heat (+115) over Nuggets — While the data doesn’t absolutely love the Nuggets, MetaNet is especially high on a Heat team that isn’t missing a single player, is playing close to home in Florida, and is led by the mentally tough and borderline insane Jimmy Butler. The Heat definitely won’t make this one easy for the Nuggets. The only reservation I have about this game is Denver’s Michael Porter Jr becoming a potential X-factor with more minutes off the bench — this one seems like a small flyer bet on the Heat to me.
Lakers (-170) over Raptors — Another game that deserves only a small flyer bet. Both neural networks didn’t particularly like the Raptors’ chances, and both neural networks ranked the Lakers among their top 5 teams. My reservation comes from the Lakers missing both starting point guard Avery Bradley and backup point guard Rajon Rondo — meaning the only “true point guard” who can chase opposing guards on defense is the rather limited Alex Caruso. The Raptors, with their deep roster of speedy guards (Kyle Lowry, Fred vanVleet) seem especially well suited to make life for the Lakers difficult as they adjust to less defense on the perimeter. The absence of Dwight Howard will be more sorely felt than people expect also — the Lakers may be forced to play Markieff Morris at center for some significant minutes, giving the Raptors’ ever-shifting lineups free rein to attack the rim. All of that being said, the data still really hates the Raptors, so they may be worth a small flyer bet out of principle.
TLDR: My neural networks say Pelicans over the Jazz, Celtics over Bucks and Spurs over Kings are great values, also likes the Magic over the Nets in spite of the awful odds, and thinks Heat over Nuggets and Lakers over Raptors is worth a small flyer.
Perhaps most importantly, after months and months without basketball, I can’t wait to start watching the NBA restart — even if it’s basketball in a bubble!
