Every March, 64 college basketball teams punch their ticket to the Big Dance—March Madness. While the bracket brings plenty of drama on the court, there’s another part of the tournament that gets less attention: how far teams have to travel for their first-round games.
We wondered: what if we could use optimization to cut down on that travel?
At SimpleRose, we build powerful optimization tools to solve all kinds of problems, from logistics to scheduling to supply chains. But just for fun, we decided to see what would happen if we asked one simple question:
What if the only thing that mattered was minimizing travel distance?
The Setup
We built a mathematical optimization model that assigns each of the 64 teams in the men’s NCAA tournament to one of the eight designated first-round game sites—while making sure each site hosts the correct number of teams and matchups.
Our objective: minimize the total travel distance across all 64 teams to their first round game.
In the actual 2025 men’s bracket, the total round-trip travel distance to the first round arenas was 102,000 miles for all 64 teams. That’s more than four times around the Earth!
Our Results
But what happens when we let our solver work its magic?
Our model keeps the tournament structure intact—1-seeds still play 16-seeds, 8-seeds still play 9-seeds, and so on—but it allows flexibility in which specific teams face each other within those seed pairings. That gave the solver room to minimize travel distance while still respecting the bracket format.
The teams can be arranged such that the round-trip travel distance is only 68,000 miles, a savings of 33%. That’s a reduction of 34,000 miles—about the distance of 14 flights from New York to Los Angeles.
Teams located within 350 miles of their game travel by bus, while the NCAA arranges charter flights for the rest. In the actual travel plan, 17 teams travel by bus. In our optimized plan, 25 teams can travel by bus. That’s a savings of 16 expensive flights.
Optimized Travel Map
The map below shows the savings from the actual travel for the 64 teams to one of the 8 first round locations compared to the results of our optimization model. In the 2025 men’s tournament, 21 teams have to travel over 1,000 miles to their game. Our model only makes 8 teams travel more than 1,000 miles.
Optimized Bracket
Here is the optimized bracket structure we generated to minimize travel distance to first-round sites. What do you think of these matchups? The numbers to the right of the team are the miles the team needs to travel to their first round game.
LEXINGTON RALEIGH
1 Auburn 380 1 Duke 18
16 Mount St Marys 118 16 Norfolk St 154
8 Louisville 69 8 Mississippi St 595
9 Baylor 844 9 Georgia 293
SEATTLE PROVIDENCE
5 Oregon 250 5 Clemson 791
12 UC San Diego 1053 12 Liberty 516
4 Arizona 1220 4 Maryland 350
13 Grand Canyon 1111 13 Yale 87
DENVER RALEIGH
6 BYU 353 6 Mississippi 619
11 Drake 608 11 VCU 139
3 Texas Tech 460 3 Kentucky 355
14 Montana 666 14 UNC Wilmington 119
DENVER PROVIDENCE
7 UCLA 838 7 Marquette 845
10 New Mexico 335 10 Vanderbilt 913
2 Alabama 1068 2 St Johns 145
15 Omaha 484 15 Bryant 9
====================== =======================
CLEVELAND WICHITA
1 Florida 819 1 Houston 562
16 Alabama St 179 16 SIU Edwardsvil 405
8 UConn 487 8 Gonzaga 1225
9 Creighton 738 9 Oklahoma 171
CLEVELAND WICHITA
5 Michigan 119 5 Memphis 448
12 McNeese 1012 12 Colorado St 461
4 Purdue 283 4 Texas A&M 492
13 Akron 31 13 High Point 965
MILWAUKEE MILWAUKEE
6 Illinois 204 6 Missouri 365
11 North Carolina 299 11 Xavier 299
3 Wisconsin 76 3 Iowa St 300
14 Lipscomb 483 14 Troy 784
LEXINGTON SEATTLE
7 Kansas 584 7 Saint Marys 676
10 Arkansas 550 10 Utah St 657
2 Tennessee 148 2 Michigan St 1857
15 Wofford 257 15 Robert Morris 2121Summary
| Actual Bracket | Optimized Bracket | |
|---|---|---|
| Total Miles | 102,000 | 68,000 |
| % Reduction | – | 33% |
| Bus Travel | 17 teams | 25 teams |
| Flights Saved | – | 16 flights |
| Teams >1,000 mi | 21 | 8 |
Why Travel Matters
Of course, the NCAA selection committee has more to consider than geography—things like seeding, TV schedules, conference restrictions, and fan bases. But this experiment highlights a key truth:
Even simple mathematical models can uncover huge savings—whether in miles, dollars, or time.
In the real world, optimization like this powers airline crew scheduling, delivery routing, supply chain design, and even renewable energy planning. The NCAA might not adopt our version of the bracket anytime soon, but the same tools can make a real impact in business.
If you’re curious about how optimization can drive smarter decisions in your business—even if it’s not about basketball—we’d love to chat.
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