There are two things we love at South Shore Analytics: sports and data. Most of all, we love when a data-first lens helps us reframe a sports story people think they already understand. If you’ve been with us for a bit, you might remember our newsletter “Why all your favorite analysts are wrong about Saquon Barkley,” where the narrative ran one way and the numbers quietly pointed towards another. With the baseball playoffs in full swing, we decided to spend this week revisiting another topic we’ve chatted about internally for years: MLB free agency. The common refrain in the media usually centers around the fact that clubs have steadily spent more to acquire the biggest Free Agents. And while that is true, it ignores the question of whether teams are spending more on a relative basis and (more importantly) if they've gotten better at buying more bang for their buck. So, naturally, we decided to crunch the numbers and find out!
For this analysis, we pulled the top ten free-agent contracts for each offseason from 2001 through 2020, tracked each player’s Wins Above Replacement (WAR) for the five seasons after signing, and normalized the shortened 2020 season. To gather this data, we relied primarily on FanGraphs.
Part 1: Spending over time, why relativity matters
If we only totaled the dollars committed to each year’s top ten Free Agents, the line climbs and the headline writes itself, which is probably why that chart shows up on TV.
This chart looks at the total $ spent on the ten highest paid FAs in each year's class
When it comes to analyzing trends on a normalized basis, however, what matters more is a relative view. To address this, we built a simple metric we call POA (Paid Over Average). For each deal, we took the average annual value (AAV) and divided it by the league’s average salary that season. The result is a clear ratio of how far above an “average” player the market paid for that signing, and it lets us compare spend over time in a much more consistent manner.
Here’s the part that surprised us when we graphed it. POA doesn’t climb in a straight line. It oscillates, sometimes sharply, but if you anchor on the endpoints you’ll notice that the relative premium in 2001 sits in the same neighborhood as 2020. In plain English, the very top of the market has been expensive for a long time. On a relative basis, these big contracts are not consistently more expensive now than they were twenty years ago.
Part 2: Analyzing the Return on Investment
To get a sense for the value that teams received for these contracts we utilized WAR - which estimates the wins a player contributes relative to a replacement level player at his position. By pulling the WAR each player produced in Years 1–5 after signing, and then dividing that by POA, we were able to arrive at a rough “wins per above-average dollar” signal. It’s not meant to be an accounting treatment, but it’s a practical way to put production and price on the same scale so we can compare cohorts and identify where the market has paid off or disappointed.
This is where the line becomes much less ambiguous. Since the early 2000s, median WAR / POA trends down. Said differently, teams aren’t paying dramatically more relative to the league than they were in 2001, but they are getting less median value back for those premium dollars. There are still great signings in every era, and you can point to eye-poppers on both ends, but when you step away from the outliers and look at the typical deal, the return curve bends the wrong way.
Part 3: So… What Gives?
Hypothesis: Are Top FAs getting older?
To figure out why teams have seemingly gotten worse at acquiring value, we started with the intuitive explanation: arbitration and control. If the CBA and team behavior keep players under club control longer, the free-agent pool should get noticeably older, and older players tend to produce less on a per-dollar basis. So, we pulled the median age at signing over time to see how this holds up. Surprisingly, this metric has actually trended down slightly - so it couldn’t be the culprit.
Result: Rejected
The lowest median ages for top FA players actually came in more recent years
Hypothesis: Increasing Share of Pitchers over time
Our next theory was that maybe the signings have trended more towards pitchers. If a larger slice of the top ten deals go to pitchers, and pitchers tend to accumulate less WAR per roster spot than everyday hitters, a mechanical drag should show up.
Overall share of position players may have decreased over time ... but not drastically so
While there is some change in composition, the pattern isn’t clean. Take 2006 and 2016: similar mixes of starters, relievers, and position players, yet the WAR/POA outcomes are very different. So there’s something else happening beyond a simple “more pitchers now” story.
Result: Rejected
Hypothesis: Shifts in Value Produced by Specific Position Groups
Our final idea was in a similar vein, but with a slightly different flavor. Maybe FA signings for a particular basket of players have done noticeably worse, and maybe that’s dragging down the totals. To test this, we grouped the signings into up-the-middle position players (catcher, shortstop, second base, center field), corner position players (first, third, left, right, DH), starters, and relievers. We then compared the performance of these groups bucketed into decades: 2001–2010 vs 2011–2020. This is where the picture sharpens. Up-the-middle players dipped a little, starters dipped a little, relievers stayed low… but corner bats fell off a cliff. The median WAR per POA for corners drops by more than half from the 2000s to the 2010s.
Count of corner position players actually increased, but the average return decreased by more than half
Why would corners specifically slide that much when the rest of the board moves only modestly? There are a few explanations that might fit what we’re seeing:
- Teams deploy roles differently now than they did twenty years ago, which means many corner signings capture fewer full-time plate appearances as managers lean into platoons and late-inning defense - and WAR tends to follow playing time
- Defensive measurement has improved, and the league got very good at positioning. This makes minus-glove, bat-first profiles more fragile in terms of above-replacement value
- On top of that, in a post-moneyball era teams have gotten a lot better at spotting replacement level talent for these more plentiful positions. As a result, the differential a premium corner bat buys over what a team can assemble internally has narrowed - even if the AAV sits at a similar multiple of the league average.
Result: We can all add our own pet theories to that list, and yes, some readers will raise an eyebrow at the early-2000s context for power numbers (ahem... steroids), but the common thread is that the typical corner signing in the 2010s returned less per premium dollar than its 2000s counterpart.
Conclusion: So where does that leave us?
Pull it together and the story is counterintuitive at first glance and very consistent once you see it. On a relative basis, teams aren’t paying meaningfully more for the very top free agents than they did in the early 2000s. At the same time, the median return on those premiums has eroded, and the steepest drop sits with corner bats, not because players suddenly got older, and not simply because teams signed more pitchers. It looks like a mix of role changes, defensive value becoming clearer, and a market that still pays for recent peaks while everyday usage narrows.
There will always be outliers. You can point to Juan Soto in 2025 on one end and Alex Rodriguez in 2001 on the other, and you’d be right to say the top of the market can still bend gravity. But our interest is in what happens most of the time, not just what makes the headline. Most of the time, the safest big-ticket bets still look like athletic, up-the-middle regulars, while reliever splurges and 1B-only sluggers rarely clear their above-average pay once the dust settles.
We’re going to keep digging into this in future issues - team-by-team patterns (spoiler: the Mets suck), how Year 1 versus Year 5 break down, and how things shift post-2020 as the run environment and rules evolve. In the meantime, we’d love to hear what you’re thinking. Have a better theory about what might be going on? Drop a comment and let’s discuss!
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