Behind the Streak: The Numbers That Really Mattered
A’ja Wilson of the Las Vegas Aces has been crowned the 2025 WNBA MVP and congratulations to her; she had a phenomenal season. In the wake of this award, one popular narrative around this award is that A’ja won because she carried the Aces to their 16-game win streak to close the regular season.
The Aces 28th game of the season was against Minnesota which ended with an embarrassing 53-point loss. After the game, the Aces went on 16-game win streak, the second longest in WNBA history and the longest in franchise history. That streak propelled the Aces from 8th in league standing with a .500 record to 2nd and a .682 standing.
A’ja’s multiple 30-point performances during this streak really did cement her name on the MVP ballot, but the question I sought to answer was: was that all there was to the streak? I am no data science wizard, but I do know my way around numbers. So let’s dig into the stats and see what — and who — really fueled the Aces’ historic run.
THE BIG 3
To answer this question, I focused on the Aces top three players: A’ja Wilson and Jackie Young, and Chelsea Gray. A’ja averaged 23.4 points per game (PPG) on 50.5% shooting, Jackie averaged 16.5 PPG on 47.5% shooting along with 5.1 assists per game (APG), while Chelsea Gray averaged 5.4 APG. A’ja and Jackie were top 2 in points, Jackie and Chelsea were top 2 in assists.
Offensively, I looked at points and field goal % (FG%) for A’ja and Jackie, as well as assists for Jackie and Chelsea. Defensively, although all 3 players were top 3 in ‘stocks’ (steals + blocks), I chose to use defensive rating (DefRTG). Stocks measure certain defensive actions, however defense extends beyond box-score stats and defensive rating is the complete way to capture those contributions. A’ja, Jackie, and Chelsea had a defensive rating of 98.8, 99.2, and 102.1 respectively.
The question we are here to answer is simple: who or what really mattered? For this, we turn to logistic regression.
THE MATH
Logistic regression is a statistical analysis method used to predict the probability of an outcome. It works by looking at how a predictor — in this case, points, FG%, assists, and defensive rating — affects the odds of an outcome — in this case, winning. For every analysis run, we get three important results:
1. P-value: This tells us whether or not the connection we see is real i.e. significant. A significant p-value tells us that the stat actually affects winning and it is not just a coincidence
2. Z-stat: This tells us the direction of the relationship. In this case, does the measured stat increase the odds or reduce the odds of the winning.
3. Odds ratio (OR): This tells us how much the stat impacts winning i.e. by how many percent does the stat affect the odds of winning.
With this, we are able to determine which stats and which players actually led to winning.
Player-Level Results
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1. A’ja Wilson: A’ja’s scoring, efficiency, and defense were strong predictors of winning. For every point she scored, the odds of winning increased by 14%, and every 1% increase in FG% increased the odds of winning by 6%. On defense, however, every 1-point increase in her DefRTG reduced the odds of winning by 12%
2. Jackie Young: For Jackie, her efficiency, playmaking and defense predicted winning. A 1% increase in her FG% increased the odds of winning by 6%, every assist increased the odds of winning by 46%, while every 1-point increase in her DefRTG reduced the odds of winning by 9%.
3. Chelsea Gray: Chelsea’s assists and defensive rating also predicted winning. Every assist increased the odds of winning by 73%, and a 1-point increase in her DefRTG reduced the odds of winning by 11%
Individually, this gave us several candidates as predictors: A’ja’s points, FG% and DefRTG, Jackie’s FG%, assists and DefRTG, Chelsea’s assists and DefRTG.
Team-Level Impact
Basketball is a team sport that consists of offense and defense so I needed to combined all the factors into one analysis to see who continued to impact winning when others were accounted for.
The Aces Big 3 log heavy minutes side by side and thus their defensive ratings were highly correlated. Instead of treating them separately, I used their average DefRTG to account for the team effort. For A’ja, points and FG% were also closely related, and to avoid overlap I chose a combined metric — PTS x FG%. While points per attempts (PPA) has been used by other analysts, it only takes into consideration the score weight of each attempt and does not account for volume.
Let’s look at the points, field goal attempts (FGA) and FG% of 4 options so we can get a better understanding:
Using PPA for the above would place C at the highest rank, however in a real game, shooter A and B would have been more impactful than shooter C. Given the fact that A’ja is the main offensive option on the Aces, PTS x FG% best accounted for her offensive load.
The final analysis looked at the impact of following — A’ja Wilson’s PTS x FG%, Jackie Young’s FG% and Assists, Chelsea Gray’s Assists, and the Big 3’s average DefRTG. When analyzed together, all these factors — except Jackie’s FG% — remained the strongest predictors of winning. Chelsea Gray’s assists had the largest impact with each assist resulting in a 7% increase in winning odds. This was followed by the Big 3’s DefRTG, with each 1-point decrease increasing the odds of winning by 6%. A unit increase in A’ja Wilson’s PTS x FG% increased winning odds by 4%, while each assist from Jackie Young increased winning odds by 3%.
THE WINNING STATS
When we compare the Big 3’s averages in wins and losses, this is how they performed.
During wins, A’ja Wilson averaged 8 more points and shot 10.8% better, Jackie Young averaged 1.8 more assists, Chelsea Gray averaged 2.7 more assists, and the Big 3 had a 20.4 point improvement in their defensive rating. Their performance during wins was undoubtedly better than during losses, and this difference was statistically significant and not the result of chance.
Within wins, there was also a small boost during the streak. Compared to the 14 wins before the streak, A’ja Wilson averaged 1 additional point, Jackie Young averaged 1.4 more assists, and Chelsea Gray averaged 2.5 more assists. Although A’ja Wilson had a slightly lower FG%, she was still well above her FG% during losses and her increased shot volume compensated for the difference.
CONCLUSION
While A’ja is the MVP and unquestionably the best player on the Las Vegas Aces, the numbers show that winning was a team effort. Offensively, A’ja Wilson’s scoring paired with the playmaking abilities of Chelsea Gray and Jackie Young fueled the Aces historic season ending win-streak. Defensively, the Big 3 stood tall as the Great Wall of Vegas, keeping losses at bay. Together, they weren’t just three standout players — they were three pieces of the same puzzle, fitting perfectly to drive the team’s success.
