Victor Wembanyama In-Game Data (2023-24)

[RedAzSa]

Hey all. I’m building a web app that offers team and player data split by various in-game pivots, and I wanted to share some interesting data points from Vic’s rookie year.

TLDR/General Themes:

• Victor’s decision-making and effectiveness were impacted by the consecutive time he had spent on the court (fatigue?)
  
  • This trend diminished as the season went on
  
  
• When playing with more fouls, Victor was less aggressive on offense but still maintained a strong defensive presence
• Victor bucked the above trends and over-performed in end-of-game/clutch moments

To start, here are a few charts that outline the Spurs overall performance on the season. This first one demonstrates how many minutes the Spurs spent within a given scoring margin:



As expected, we spent the majority of our minutes under water. Looking at our +/- split by each of the 48 minutes, however, you can see that we generally started (+106 overall in the first 5 minutes of the game) and finished (+88 overall in the final 6 minutes) strong. Everything in between was reliably brutal.



Now looking at Victor’s stats, here is a chart of the minutes he played per each of the 48:



He had a clear trend of playing the first 5-6 minutes of every quarter then subbing out. When the game was close down the wire, he was in.

The next series of charts pivots the data based on the duration of Wemby’s current stint. His first minute on the floor of a given stint (at the start of the game or after subbing back in) goes in the “1” bucket and so on. Here is the team’s +/- over each of the buckets



With this dataset, keep in mind that the farther right you go, the smaller the sample size. The 12th minute bucket, for example, only has a total of 9.78 minutes, whereas the 5th minute bucket has 274.28 minutes. It’s also worth noting that Victor really only played in these extended stretches during close finishes/overtime. These larger minute buckets tend to skew towards “clutch” moments.

Here, you can see that the spurs generally held their own in the first 5 minutes Wemby was on the court. After this, however, there was a pretty big drop off. In his 7th minute, for example, the Spurs were -57 in 135.95 total minutes.

Some interesting data points on this pivot are shot selection and field goal percentage. The below chart shows that for the majority of the season (October - February), Victor generally shot farther from the basket as his time on the court ticked up:



The implication here is that as he fatigued, he preferred to pull up and shoot a long jumper rather than battle for position down low. Here is his field goal % during the same splits:



In addition to shooting tougher shots, his 3pt percentages also dipped after more time on the court. In the first 4 minutes on the court, Victor made 59 of 169 threes (35%). After that, this dropped to 30 of 99 (30.3%).

In March and April, however, Victor really found his rhythm and these trends aren’t quite as clear.






He was playing longer stints, and his conditioning seemed notably improved.

There was also a trend throughout the season of Victor deferring more the longer he was on the court.



In his first minute of action, he logged 24 assists in 334.7 minutes (0.072 per minute), but by the 8th minute he had 16 assists in just 91.2 minutes (0.175 per minute).

The next dataset I found interesting relates to his foul count throughout the game.



In the 950 minutes he played with 0 fouls, Victor took 596 shots (0.627 per minute). In his 45.6 minutes with 4 fouls, he only took 16 (0.351 per minute). Keep in mind that when on the court with 5 fouls, that probably means crunch time. In these minutes he took 0.524 shots per minute.



There’s an even more dramatic drop off when looking at assists per minute across foul count. In general, Victor was less involved on offense as he racked up fouls.

When protecting the rim, however, it didn’t really matter how many fouls he had.



He continued to swarm shooters and blocked an insane 0.21 shots per minute when playing with 5 fouls.

Disclaimer: This is still a work in progress and there may be bugs I haven’t come across yet (I know there are a few typos in the chart labels). The images are a bit grainy since I had to shrink them to fit the forum.

[Seventyniner]

Great stuff!

[exstatic]

Good luck competing with BBREF’s Stathead.

[DAF86]

Looking at our +/- split by each of the 48 minutes, however, you can see that we generally started (+106 overall in the first 5 minutes of the game) and finished (+88 overall in the final 6 minutes) strong. Everything in between was reliably brutal.

I have a theory that blames this on Pop's mad scientist rotations. He picks and chooses way too much, he doesn't let players get in a rythm; he plays the bench way too much and the starters way too little. It's no wonder the two times the starters are usuallly in the game (start and finish) the team did well.