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Statistics to Help the Spurs


Every sports fan, diehard or casual, has watched Moneyball, the movie about the use of statistics in baseball. While sports has become more receptive to the use of statistics to identify players, many fans still do not like to use or misuse statistics to back up their opinions. As an avid NBA fan, I too love to concoct fictitious trades to help make my team better. Through the use of statistics, I am going to try to make well informed decisions regarding player acquisitions for the San Antonio Spurs, my favourite NBA team. To tackle this problem, I used a linear regression model.

To create the model, I first collected box score data for the Spurs’ 2019-20 season. This data was then used to create a model that will give a composite score, which predicts a team’s record. According to the model, a score closer to 1 indicates a better record, while a score closer to 0 indicates a worse record. Using Basketball Reference, I identified 8 players who the Spurs could feasibly acquire and who would improve their record. Then, I extrapolated all of the thirteen players’ stats to 48-minute stats, this is useful because it focuses on if the main 5 played all 48 minutes of a game, which delivers a better estimate of the team’s quality. As it is almost impossible to completely change a team’s roster within one season, I limited the number of new additions to either 1 or 2 players.

The 13 players involved in this are the San Antonio Spurs main 5 (Dejounte Murray, Bryn Forbes, DeMar DeRozan, Trey Lyles and LaMarcus Aldridge) and 8 other players who I thought could join the Spurs. The players are Malik Monk, E’Twaun Moore, Otto Porter Jr., Will Barton, Aaron Gordon, Dario Saric, Mo Bamba, and Montrezl Harrell.

When the model was run, the top team consisted of Murray, DeRozan, Aldridge, Gordon, and Barton. The aforementioned team achieved a score of 0.802, while the Spurs current main 5 achieved a score of 0.579. DeRozan and Murray were present in all of the top 10 results, and Aldridge was in 7 out of the 10. Will Barton was in five of the top 10 results, and Aaron Gordon was in 7 of the top 10. Mo Bamba was in 4 of the top 10, though this can be attributed to his amazing blocks numbers in limited playing time. Most of the best results substituted Bryn Forbes and Trey Lyles for Gordon or Barton. These are the 10 best lineups, with their Win Co-Efficient.

 



 On the other hand, the 10 least productive lineups according to the model all featured Bryn Forbes, LaMarcus Aldridge and Trey Lyles. These lineups mostly failed due to a lack of passing, and all the lineups had two Lou Williams-type ‘Professional Scorers’ (Bryn Forbes and Malik Monk/E’Twaun Moore) and three big men. Otto Porter Jr., who makes two appearances in the 10 least productive lineups, also possesses sub-par passing ability. In fact, none of these lineups had more than 18.5 assists. They are listed below along with their Win Co-Efficient.

 


A quick study shows that the Spurs should likely let Bryn Forbes play in his natural sixth man role, where he can be best utilized as a gunner and 3-point specialist, and trade for Aaron Gordon or Will Barton. This will allow the Spurs to strengthen positions of need without gutting the rest of their roster. The data shows that the Spurs, while unlikely to win a championship in the near future, can contend for a spot in the Western Conference playoffs with a few savvy trades, and can keep their record 22-year playoff streak alive.

In an upcoming article, I will also be detailing the trades that the Spurs could make to acquire the players I identified as reasonable targets.

Comments

  1. Cool - this is interesting. Can I use this to determine my fantasy team too?

    ReplyDelete
    Replies
    1. Thanks. You can certainly use it if you want to. Thanks for the feedback.

      Delete
  2. Some intense dissection here!

    ReplyDelete
  3. Although I do not follow basketball much, I am quite familiar with mathematical modeling. The article very clearly explains the modeling technique and the conclusions. Additionally, there are hints on the strengths and weakness of the modeling approach.

    The analysis is thorough and written in a lucid style.

    Very impressive!!

    ReplyDelete
  4. The article was very informative and give clear picture of the scenario. Excellent narration. I am proud of you Ratnam.

    ReplyDelete

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