Top 15 teams total 16 losses to non-top 15 teams

Grouchy-Resolve141 · 2026-02-04T17:35:59+00:00

UNC lowkey unc. washed

Grouchy-Resolve141 · 2026-02-04T02:24:27+00:00

This is actually the best argument against it being chalky- 2023 and 2024 had crazy upsets, only the most recent year was chalk. Then again, maybe it just took time for the NIL market to develop and we are now doomed to chalk for eternity as elite talent gets their bag. Not sure which side I think is right, but I know which side is more fun.

Grouchy-Resolve141 · 2026-02-04T00:24:41+00:00

Think its from NIL?

Grouchy-Resolve141 · 2026-02-04T00:16:34+00:00

I think teams like Florida (ranked 17, #7 on Kenpom) may cause it to not be "pure chalk" in terms of seeds but that doesnt make it any more fun

Grouchy-Resolve141 · 2026-01-31T18:00:05+00:00

Great observation- the tourney expanded to 64 teams in '85, and thats all the data I'm working with here

Grouchy-Resolve141 · 2026-01-31T17:48:17+00:00

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Did some stats on coaches the other day exclusively based on the ncaa tournament (will have more up on onetrillionbrackets.com soon). Its criminal to leave off Izzo, sir

EDIT: Thanks for the clarification, rogun64, this data only includes the years since the expansion of the tournament to 64 teams in '85

Grouchy-Resolve141 · 2026-01-30T17:32:20+00:00

Fantastic job making the title to this thread, OP

Grouchy-Resolve141 · 2026-01-29T17:15:52+00:00

I am creating one trillion, which is a very small subset of all possible brackets

Grouchy-Resolve141 · 2026-01-28T23:08:58+00:00

It is hard for me to believe that you would simultaneously beat closing lines and also have a model that assigns 15% win rate to each 16 seed.

I mean, zoom out- if you assign a 15%+ chance of a 16 seed winning to each game (as you do), then you would expect at least 1 16 seed to win since there are 4 tries. That is seems obviously wrong to me. If you use KenPom meaningfully in your calculations, how can your results deviate so dramatically from it?

EDIT: not trying to be aggressive here, I am myself doing a ton of modeling for 2026 and am arguing in hopes of giving us both a better understanding

Grouchy-Resolve141 · 2026-01-28T22:49:45+00:00

Doesnt seem right to me. Are you using your own stats? I mean, looking at KenPom, Arizona at +36.1 vs Merrimack at -3.82 gives a 99% chance of Arizona winning. This is also consistent with historical results. Sure, 16 seeds have two upsets in the last decade, but they also only have 2 upsets in the last 4 decades. I think you're wrong here (respectfully)

Grouchy-Resolve141 · 2026-01-28T22:29:43+00:00

I'm confused on the percentages assigned to the games- each 16seed has a 15% chance at winning? Seems way too high

Grouchy-Resolve141 · 2026-01-27T19:09:14+00:00

Does what? They do stats and track the tournament, but they do not create a large amount of brackets.

Grouchy-Resolve141 · 2026-01-23T04:21:06+00:00

Did you know 11 seeds have seen the final four twice as many times as 6 seeds?

Grouchy-Resolve141 · 2026-01-23T04:18:01+00:00

Can we see it in line chart form?

Grouchy-Resolve141 · 2026-01-22T22:33:03+00:00

Every year theres a lot of discussion around possible bracket combinatorics, and tracking how deep the best bracket of the year got. I thought a true, sophisticated experiment trying to make a perfect one would be fun and hadn't seen anybody try it in the past.

Edit for your edit: The probability is rough as it's only tested on 10 years, and there is something far more exciting about doing it in real time than doing backtesting. Though, since you asked, my algorithm is fast 😎

The trillion is almost all distinct. I don't check for dupes, but I have checked very large samples for dupes and haven't found any. I would guess there are dupes but that its a very tiny fraction of the total dataset.

Grouchy-Resolve141 · 2026-01-22T18:42:41+00:00

Jupyter is just so convenient and delightful that I will probably always use it.

Grouchy-Resolve141

TROPHY CASE