NBA award voters, ranked
Which voters march to the beat of their own drum and which just follow the crowd
There’s a couple of interactive tables in this post that are best viewed in your web browser instead of your email client. Just click the title of this post to open it in your default web browser.
Now that the NBA award ballots have been published, it’s time to conduct my ranking of award voters by how contrarian their choices were. My methodology is in the footnotes1, but the general idea is to see how many points a voter awarded a player and see how much that differs from the average number of points that player received from everyone else that had a vote. The further the point total from the average, the higher a voter ranks on my Contrarian scale. There’s a little more to it than that, and I encourage you to read the footnotes if you care about the nitty-gritty, but that’s the gist of it.
Anyway, the table below ranks all 100 award voters by their total Contrarian Score. I’ve broken each voter’s Contrarian Score out by each award so you can see what specific ballot is driving their Total Contrarian Score up or down.
For example, Stan Van Gundy had the most unique collection of ballots relative to his peers this year. His high Contrarian Score is largely driven by his Sixth Man of the Year, Coach of the Year, and Most Improved Player of the Year ballots. Here are some choices he made that stand out.
Voting Payton Pritchard third for Sixth Man.
Pritchard won the award, receiving an average 4.5 points from the other 99 voters. So Van Gundy’s Contrarian Score went up because his third place vote was worth less than the average Pritchard received.
Voting Tye Lue first for Coach of the Year.
The average voter gave Lue just 0.3 points for Coach of the Year.
Voting Josh Giddey first for Most Improved.
Only four other voters even put Giddey on their MIP ballots and none higher than second place.
To be clear, I don’t think any of Van Gundy’s votes were controversial even if they were particularly unique. They’re all more than defensible in my opinion.
It’s worth emphasizing that being contrarian is not a bad thing. In fact, a healthy amount of contrarianism that comes from having an original opinion is probably good for the league and award voting at large. Although I’m not sure the NBA agrees.
Flavio Tranquillo of Sky Italia was the second most contrarian voter this year. It was their first time voting since 2019 and it would not shock me if it were also their last. That’s because last year’s most contrarian voter, Tolis Kotzias of SDNA, was not given an award ballot this year. Similarly, Eduardo Barao of BAND, the most contrarian voter of 2023, did not receive an award ballot in 2024 or this year. It seems as though the quickest way to lose your ballot is to be a member of the foreign press and go against the grain.
If voters want to ensure they keep their ballot they should probably take a page out of Jason Beede’s book. Beede, an Orlando Magic beat reporter, was this year’s least contrarian voter. None of Beede’s votes strayed too far from consensus. His least conventional decision was moving LeBron James and Steph Curry to Third Team All-NBA and Karl-Anthony Towns and Cade Cunningham to Second Team. Not exactly controversial stuff.
The above table is interesting, but useless without a complementary table that allows you to look up every vote cast by every voter and see how far their individual vote differed from the consensus. So that’s what I’ve put together below. Use this in conjunction with the earlier table to see why a voter ranked high or low on my Contrarian scale.
Big shoutout to reddit user cilantro_samosa for their github repo that collected and cleaned all the award ballots and put them in one place. They have all the award ballots going back to 2014 on their repo. Great resource for anyone looking to dive into this data themselves.
It’s a Copycat League
Now I want to talk about what I think is the most interesting takeaway from the awards data. We can use the results to see which award had the most amount of distinct ballots. By distinct, I just mean either the players or the order of the players on the ballot were unique.
Naturally, the All-NBA, All-Defense, and All-Rookie awards have more unique ballots because there are more possible unique combinations. Voters select 15 players to All-NBA and ten players each for All-Defense and All-Rookie. So we’d expect there to be more distinct ballots compared to the other awards.
But if we just look at the awards where voters had to select between three and five individuals we find that there is the least amount of herd behavior in the Most Improved Player (MIP) and Defensive Player of the Year (DPOY) voting. I’m not surprised. MIP is an ambiguous award without a coherent definition. No one knows if it’s meant to reward a role player that’s developed into a star or just a high pedigree player that’s finally lived up their draft slot. Meanwhile, DPOY is another eye of the beholder award. Voters can’t as easily rely on stats to judge who’s worthy because defensive stats are still fairly flawed. So it’s not a coincidence that the MIP and DPOY awards have the least amount of unique ballots and therefore the least amount of groupthink.
Meanwhile, the MVP award, which requires voters to select a total of five players to each ballot, had the second fewest unique combinations. Only the Rookie of the Year ballots had more consensus. I think that speaks to the amount of groupthink that plagues MVP voting. It’s the one award that drives NBA conversations throughout the year. By the time awards voters actually cast their ballots, they already know who they’re “supposed” to vote for because the consensus top five has long already formed.
Voters can vote however they want, but they’re increasingly voting more alike than different. The chart below shows the number of unique MVP ballots by season. This year saw the least amount of unique MVP ballots (both on a total and per voter basis) since 2014 — the first year the NBA started publishing ballots.
We can also look at it in a slightly different way: how many voters submitted identical MVP ballots each year?
This year, 36 different voters had the exact same MVP ballot one through five (1. Shai Gilgeous-Alexander; 2. Nikola Jokić; 3. Giannis Antetokounmpo; 4. Jayson Tatum; 5. Donovan Mitchell). Before this year, there had never been more than 17 voters in a season with the exact same MVP ballot one through five.
In other words, voters aren’t just putting the same five players on their MVP ballots. They’re increasingly putting the same five in the same order on their MVP ballots. We’re not just seeing a consensus forming around the top two vote getters in the MVP race. We’re now seeing the effects of groupthink trickle all the way down to the bottom of the MVP ballot.
The results from the chart above are especially surprising when you consider that there are about 25-30 fewer voters in 2025 than there were ten years ago. You would expect that as the number of voters has decreased, the number of voters having the exact same ballot would decrease as well. But that wasn’t the case this year.
The MVP race has never been more predictable and thus never been less interesting. Part of that is because voters have gotten smarter. NBA data is better and more accessible than it was in the past so more voters can make the analytically “correct” choice. Part of it is because ESPN runs a straw poll every two months to tell voters who’s in the lead and who’s fallen out of the race. But an even bigger reason I think is that no voter wants to be clowned for going out on a limb, which might result in them having their ballot taken away.
All year I wondered if we would see less groupthink this season because Zach Lowe was absent from the day-to-day NBA coverage. When I’ve done this analysis in the past, I’ve found that Lowe regularly scores fairly low on the contrarian scale and I suspect it’s because many of his peers read and listen to him to form their own opinion before voting. But we saw the opposite in the MVP race this year. Even more groupthink. More herding. More than a third of the NBA’s voting body had the exact same MVP ballot!
Maybe the problem isn’t the voters, but the structure of the award voting itself. When the stakes of being wrong are high (both reputationally and professionally) it’s probably smart to vote boring. But the NBA awards are meant to tell the story of a season. And stories this boring aren’t worth reading.
Best way to explain how this system works is with an example:
Giannis Antetokounmpo received one first place vote for Defensive Player of the Year this season, which was worth a total of five points. It was the only DPOY vote Giannis received and it was given to him by Ric Bucher.
The first step is to subtract the total points Bucher assigned to Giannis from the average DPOY points Giannis received from all other media members, not including Bucher.
5.0 - 0.0 = 5 point difference
To “ding” particularly contrarian votes, I squared that number. That means giving Giannis a first place vote for DPOY when he wasn’t on any other ballots is worse than giving a first place vote to Draymond Green, who finished third in the voting.
5.0 * 5.0 = 25.0 point difference
To continue to use Bucher’s DPOY ballot as an example, he gave Bam Adebayo three points (Adebayo received zero votes from other media members) and Evan Mobley one point (2.86 points per media member).
Antetokounmpo: (5 - 0)^2 = 25.0
Adebayo: (3.0 - 0)^2 = 9.0
Mobley: (1.0 - 2.86)^2 = 3.5
Importantly, we also want to account for the votes that Bucher didn’t make as well. For example, he left Dyson Daniels off his ballot entirely. But Daniels received 2.0 point per media member. So we need to include those squared differences as well for all the players that received votes for DPOY.
Dyson Daniels: (0 - 1.99)^2 = 4.0
Draymond Green: (0 - 1.55)^2 = 2.4
Lu Dort: (0 - 1.10)^2 = 1.21
Amen Thompson: (0 - 0.93)^2 = 0.88
Ivica Zubac: (0 - 0.34)^2 = 0.11
Jaren Jackson Jr.: (0 - 0.09)^2 = 0.008
Toumani Camara: (0 - 0.04)^2 = ~0.001
Derrick White: (0 - 0.03)^2 = ~0.001
Shai Gilgeous-Alexander: (0 - 0.03)^2 = ~0.001
Rudy Gobert: (0 - 0.01)^2 = ~0.0001
Next, I took the square root of the average of those point differentials for every vote/non-vote to create a Contrarian Score for that specific ballot.
Then we can sum up all those ballot specific Contrarian Scores to find each voter’s Total Contrarian Score.
The higher the Total Contrarian Score, the further a voter’s assortment of ballots tended to deviate from the consensus.
Check out this article about NBA groupthink! It covers a lot of the same points you talked about:
https://open.substack.com/pub/basketballpoetry/p/the-stunning-numbers-behind-the-mvps?r=3tacxx&utm_medium=ios
would be interesting to see how individual voters' contrarian behavior changes over time. i'd assume most folks get more contrarian over time, but maybe some folks get pushed back to the herd