For my money, we are all of the cusp of the best three weeks of the entire year. We just wrapped up two weeks of conference tournaments, but those were just an appetizer to the main course that is to come.

The powers that be gave us the menu on Sunday evening. Now it is time to enjoy a brief break and palette cleaner before we all make our selections. But what shall we choose? Which tasty little upset looks the best in the first round? Which teams are most likely to be sweet in the second weekend? Which quartet will comprise the final course?

Over the years I have developed a set of tools that I use to gain a better understanding of the mathematical underpinning of the NCAA Basketball Tournament. My methodology has a solid track record of correctly identifying upsets and sometimes doing more than that. In 2023, I used data to correctly predict that No. 4 seed UConn would win the National Title.

There is no foolproof way to dominate your office pool. My method reveals that the dice are loaded (and by how much), but each game is still a roll of the dice. But my method does provide some helpful hints as to the more likely March Madness scenarios. While we wait for the feast to begin on Thursday at noon, "Dr. Green and White" is here to help you fill out your 2025 bracket.

Before we did into the current bracket in detail, let's start with an overview of my methods and general trends to expect in 2025.

The foundation of my methodology is an observation that I made several years ago. It boils down to this:

When it comes to NCAA Tournament upsets, the behavior is exactly the same as in regular season games. The odds are largely predictable based on Vegas points spreads and by tools that can predict point spreads, such as Kenpom efficiency margin data.

My analysis of college basketball odds is based on this premise. Kenpom efficiency data can be used to assign probabilities to any arbitrary basketball match-up. Knowing this, the full season and any tournament can be mathematically modeled and its odds can be calculated.

My favorite plot to highlight this fact is shown below.

This figure compares the winning percentage for the higher seeds in the NCAA Tournament to the odds expected based on the average point spread for games with that seed combination. The figure shows that data for all seed combinations that have occurred at least 40 times.

Figure 1 tells us why No. 16 seeds have won two times over the past 39 tournaments (1.3% of the time). It is because on average No. 16 seeds are 22.5-point underdogs and 22.5-point underdogs win straight up 1.4% of the time whether the game in played in March or in November.

There are a few notable deviations from this correlation. For example, No. 10 seeds have surprisingly good luck against No. 2 seeds and No. 9 and No. 5 seeds do not upset No. 1 seeds in the second round or in the Sweet 16 as often as expected. As Figure 1 shows, the overall correlation is very strong.

The Vegas points spreads and the point differentials predicted by Kenpom efficiency margins also correlate very strongly. Figure 2 below shows how strong this correlation is for the first-round games in the 2025 NCAA Tournament.

Figure 2 gives us confidence that Kenpom efficiencies can be used to model the results of the NCAA Tournament.

Sometimes we can get a sense of how "mad" the NCAA Tournament will be based on the results of the conference tournaments. Of the 31 total conference tournaments, 17 were won by the No. 1 seed (55%), 11 were won by the No. 2 or No. 3 seed (35%), and only three were won by a No. 4 seed or lower. The favorites did much better in conference tournaments than the trend in 2024.

Will this translate into a calmer March Madness, or does this mean that Cinderella is bit stronger this year?

I attempted to explore this question by simulating the results of the 2025 tournament 5,000 times and counting the number of upsets that occurred in each round. I then compared these values to simulations of previous tournaments and to the results of the past 22 actual tournaments. The results are shown below in Figure 3.