About this report
This report applies a proposed MLB salary cap and salary floor to current public payroll estimates and standings.
It is a simulation, not a prediction. It does not try to normalize benefits, forecast trades, guess future roster moves, or predict the final language of a collective bargaining agreement because that's impossible. The last time that owners proposed a salary cap was in 1994 and that lead to a World Series being cancelled. Cancelling the World Series is a serious thing for owners and players. 1994 was only the second time in history that a World Series has been cancelled. Even World War II when great players like Ted Williams were off fighting, the World Series went on. So in all honesty, I don't believe in this salary cap enough to do a proper simulation. So, this is just for fun.
Which is great because it means that my point can be simple:
If these cap and floor numbers were applied to current public payroll estimates, what would the league look like?
The result is messy. Several winning low-payroll teams would be forced to add payroll. Several losing high-payroll teams would be forced to cut payroll. The league-wide net payroll change is almost flat, but two-thirds of the league would be pushed into some kind of payroll change.
Why this is interesting
Salary caps and floors are usually discussed as competitive balance tools. That sounds tidy until the numbers meet actual baseball.
A team can spend heavily and lose. A team can spend carefully and win. A team can be under the simulated floor while holding a playoff position. A team can be above the simulated cap while sitting outside the playoff picture.
That does not prove a cap and floor would be good or bad for baseball. It does show that the current standings do not make a simple case that high payroll equals competitive dominance or low payroll equals competitive failure. It also shows a lot about why baseball is such a beautiful game. In a 162 game season, raw talent and prior results don't always mean a lot. Injuries are a major problem, team chemistry is a major problem and teams can get hot at an appropriate time and go far. Or teams can get cold at the worst possible time and kill their entire season in a month. If we just ranked teams by payroll, baseball would be boring as hell.
How to read the table
The table combines current standings, public payroll estimates, and simulated cap/floor calculations.
The main fields are:
- Luxury tax projection: the payroll estimate used for the simulation.
- Simulation status: whether the team is above the cap, below the floor, or inside the band.
- Required change: the amount the team would need to cut or add in this simulation.
- Cost per win: luxury tax projection divided by current wins as of May 28, 2026.
- Wins per $100M: current wins scaled by payroll.
- Payroll-record gap: the gap between payroll rank and MLB record rank.
These numbers are not a final verdict on team quality. They are a snapshot taken the end of May. While the early season matters, it's the dog days of July and August where teams really start to separate from each other. This is just a snapshot.
Methodology
The report uses:
- Current detailed standings from MLB.com.
- Public payroll estimates from FanGraphs RosterResource.
- The simulated cap and floor values stored in the report data.
- The luxury tax projection as the primary payroll field.
The calculations are intentionally simple. A team above the simulated cap is marked as needing to cut payroll. A team below the simulated floor is marked as needing to add payroll. A team between the two numbers is marked as within the band.
This report does not normalize benefits because public payroll tables and CBA proposal language do not necessarily define benefits the same way. And most importantly, the owners threw a $23.5 million dollar per team benefits amount out during their announcement. Knowing the MLBPA, they're not going to be into a salary cap at all but the only thing that could possibly move that would be extremely expanded benefits so the $23.5 million dollar amount doesn't look reasonable. Further, this simulation does not try to model trades, deferred money, contract options, arbitration changes, injuries, or future free agency. It's as simple as you can get and uses such fancy data mangling tool as addition, subtraction and multiplication. :)
Accessibility notes
This report is built around text and tables first. The summary cards are convenient, but the full table contains the real data because a buddy in my Fantasy League is blind and he has a lot of trouble accessing this type of information. So I don't know... maybe some of you folks who have all this data on your websites could maybe try using a screen reader. It would really help a really good dude who doesn't get to use certain data source because he's blind. I'm no expert but I think there's even something an ADA which applies. But hey, enough of that and onto baseball.
The table can be searched and filtered. The result count updates after filtering. The data is also presented with normal headings, captions, and table headers so screen readers can move through it without depending on color or chart-only meaning.
Most importantly, you can't just learn accessibility. Instead it is a lifelong process and so I am still learning. If I make a mistake and something doesn't work, first off, I'm sorry, I really tried. And second, please contact me so that I can fix this. As you can tell from my first paragraph, accessibility is really important but I am neither blind nor visually impaired and so I'm not as good with screen readers as you are. Please accept my apologies and please help me fix my mistakes.
And what did we learn?
A cap and floor may change payroll distribution, but current standings do not make a simple case that high payroll equals competitive dominance or low payroll equals competitive failure. We're still into May and so next step, I'm going to take the money analysis into prior seasons.
And so while we haven't really learned enough to make any conclusions beyond 'wow, this will be chaos', I will use this methodology in past seasons to attempt to come up with data on how much spending actually matters over several full seasons.