Which Types of Teams Are Signing Free Agents?
Here’s a narrative you’ve probably heard this offseason: free agency is back because non-playoff teams are trying to make a splash. On its face, it makes a lot of sense; the Angels, White Sox, Rangers, Reds, and Diamondbacks have all made meaningful additions to their rosters this year. Star players are headed to non-playoff teams, hoping to tip the scales of 2020 in their favor.
And yet, that narrative leaves out some inconvenient truths. Of the top three free agents this offseason in our Top 50, two signed with playoff teams. Sixteen free agents who were worth 2 or more WAR last year have signed so far; of those 16, 10 are headed to teams who played in October this year.
Only last year, all three of the top free agents (Manny Machado, Bryce Harper, and Patrick Corbin) signed with teams who hadn’t made the playoffs the previous year. Is the 2019-2020 offseason truly the year of non-playoff teams getting fancy, or are we merely falling victim to narrative?
I decided to look at this question a few different ways, because it’s a complicated issue. First, I painted with a broad brush. I took every offseason free agent signing since the end of the 2001 season. I looked at their previous season’s WAR, as well as whether the team signing them made the playoffs the previous season. From there, I simply calculated a ratio; what percentage of free agency WAR was added by playoff teams?
| Offseason | Total Free Agent WAR | % Acquired By Playoff Teams |
|---|---|---|
| 2002 | 124.4 | 44.8% |
| 2003 | 150.6 | 37.8% |
| 2004 | 197.2 | 28.4% |
| 2005 | 178.1 | 40.9% |
| 2006 | 122.8 | 25.1% |
| 2007 | 126.4 | 38.1% |
| 2008 | 88.2 | 41.3% |
| 2009 | 124.6 | 39.9% |
| 2010 | 128.7 | 44.8% |
| 2011 | 137 | 40.5% |
| 2012 | 107.4 | 29.1% |
| 2013 | 116.6 | 37.7% |
| 2014 | 116.7 | 28.0% |
| 2015 | 87.3 | 26.6% |
| 2016 | 120.4 | 47.0% |
| 2017 | 80.1 | 45.6% |
| 2018 | 114 | 39.6% |
| 2019 | 122 | 35.9% |
| 2020 | 84.5 | 56.6% |
Hmmm. That’s not what you would expect to see. This offseason, so far, has been the most playoff-team-biased free agency period since the start of our sample. And it’s not even particularly close — this year is the strongest winner-take-all free agency market by more than 10 percentage points.
Okay, so that’s not what we expected. No need to get discouraged just yet — let’s try it another way. What if we only looked at above-average players signing? Maybe the flood of mediocre free agents signing with mediocre teams distracts from the key narrative, a hundred hangers-on overcoming the few bright stars of free agency. Let’s do this analysis again, only this time we’ll only look at players who accrued 2 or more WAR in their last year before free agency.
| Offseason | Total Free Agent WAR | % Acquired By Playoff Teams |
|---|---|---|
| 2002 | 81.2 | 45.7% |
| 2003 | 102.5 | 40.0% |
| 2004 | 145.2 | 31.5% |
| 2005 | 122.1 | 46.9% |
| 2006 | 74.8 | 22.6% |
| 2007 | 75.6 | 41.1% |
| 2008 | 59.2 | 53.2% |
| 2009 | 83 | 44.1% |
| 2010 | 78.8 | 56.1% |
| 2011 | 94.2 | 44.9% |
| 2012 | 70.1 | 34.7% |
| 2013 | 85.9 | 37.5% |
| 2014 | 83.6 | 27.2% |
| 2015 | 56 | 22.7% |
| 2016 | 86.6 | 51.0% |
| 2017 | 52.7 | 49.5% |
| 2018 | 67.8 | 32.7% |
| 2019 | 69.3 | 33.9% |
| 2020 | 61.5 | 58.6% |
Well gosh darnit, still nothing. Stripping away the chaff goes in the general direction we would expect (playoff teams sign a higher weight of stars than of overall players), but 2019 still looks extremely top heavy.
Let’s double back. A binary distinction between playoff and non-playoff teams is crude. Let’s replace it with winning percentage, an elegant metric for a more civilized age. I took each team’s winning percentage and weighted it by their share of the free agent market in each year to get a weighted winning percentage for the teams signing free agents. For example, if a .750 team and a .250 team each signed a 3 WAR player and that was the entire free agency period, the weighted winning percentage would be .500. If instead the .750 team signed a 3 WAR player and the .250 team signed a 1 WAR player, the weighted winning percentage would be .625.
| Offseason | Weighted Winning Percentage |
|---|---|
| 2002 | 0.541 |
| 2003 | 0.534 |
| 2004 | 0.497 |
| 2005 | 0.521 |
| 2006 | 0.491 |
| 2007 | 0.509 |
| 2008 | 0.524 |
| 2009 | 0.522 |
| 2010 | 0.520 |
| 2011 | 0.525 |
| 2012 | 0.509 |
| 2013 | 0.507 |
| 2014 | 0.505 |
| 2015 | 0.494 |
| 2016 | 0.524 |
| 2017 | 0.508 |
| 2018 | 0.500 |
| 2019 | 0.509 |
| 2020 | 0.545 |
Nothing, huh? Okay, let’s do it again, but add in our “only good players” filter from before. Here’s the weighted winning percentage of the teams good free agents are joining — only signings of players worth 2 WAR or more count:
| Offseason | Weighted Winning Percentage |
|---|---|
| 2002 | 0.557 |
| 2003 | 0.545 |
| 2004 | 0.501 |
| 2005 | 0.531 |
| 2006 | 0.497 |
| 2007 | 0.511 |
| 2008 | 0.537 |
| 2009 | 0.532 |
| 2010 | 0.533 |
| 2011 | 0.530 |
| 2012 | 0.516 |
| 2013 | 0.508 |
| 2014 | 0.506 |
| 2015 | 0.500 |
| 2016 | 0.529 |
| 2017 | 0.513 |
| 2018 | 0.494 |
| 2019 | 0.511 |
| 2020 | 0.548 |
Sigh. Looks like we’re not getting to the answer I want in any obvious way. But wait! What if what my brain is really telling me is that more teams like the Diamondbacks and Reds are getting involved? Let’s set their 2019 records — 85 and 75 wins, respectively — as our boundaries and see whether teams in that range are more aggressive this year than before:
| Offseason | Cuspy Team Acquisition % |
|---|---|
| 2002 | 13.9% |
| 2003 | 28.0% |
| 2004 | 24.1% |
| 2005 | 15.1% |
| 2006 | 37.9% |
| 2007 | 37.7% |
| 2008 | 21.2% |
| 2009 | 19.7% |
| 2010 | 27.5% |
| 2011 | 29.0% |
| 2012 | 17.9% |
| 2013 | 17.0% |
| 2014 | 21.2% |
| 2015 | 27.7% |
| 2016 | 40.2% |
| 2017 | 24.8% |
| 2018 | 31.9% |
| 2019 | 33.0% |
| 2020 | 23.5% |
Alright, I give. There’s surprisingly little in the data to tell the story of more free agents heading to teams striving for the playoffs. Some of this is a game of endpoints and definitions, of course: the Angels won 72 games last year, so they count as a bad team in this analysis, but their signing of Rendon probably fits the spirit of a team on the cusp.
Similarly, the Brewers made the playoffs last year, but any signings they make probably belong in the same breath as the Diamondbacks, who were all of four wins worse last year but had better underlying numbers. My outlined system puts them in the same bucket as the Yankees, which sounds weird. There are bound to be bright lines somewhere, and that could certainly goof with the analysis.
For the most part, however, the real story is that nothing much has changed. Teams in the middle always sign free agents, and this year seems mainly notable for how early everyone has signed, not where they’ve signed. Take a look at the proportion of free agents joining teams who fit into the broad categories of Bad (fewer than 75 wins), Cuspy (75-85 wins), and good (more than 85 wins) since after the 2001 season:

The more things change, the more they stay the same. This offseason doesn’t look markedly different than the past; if anything, we appear to be in a cyclical high of free agents joining already-good teams, potentially a consequence of the tanking-or-great stratification of baseball.
One caveat to this analysis: not all the free agents have signed yet! 21 of our top 50 free agents remain unsigned, and there’s nearly 50 WAR worth of unsigned free agents kicking around all told. Where those players go can still tilt this analysis in one direction or the other.
But based on what’s happened so far, my intuition isn’t in agreement with the data. Major league baseball might well be getting more competitive. The cycle of boom and bust team-building and juggernauts hoovering up all the talent may be coming to an end. But if it is, it hasn’t yet shown up in free agency this year. The good teams are acquiring as many free agents as they ever have, even if a few notable exceptions to the rule have made this offseason exciting.
This article has been updated to reflect minor changes in data collection involving Wild Card teams, multiple players with the same name signing in the same offseason, and individual players signing more than once in the same offseason. The changes don’t affect any of the text; only the first three tables have been updated.
Ben is a writer at FanGraphs. He can be found on Bluesky @benclemens.
Ben, more great work. I love the way you manipulated statistics in search of narrative support- a real lesson for all of us. Sometimes the data are what the data are…
A good way to check the resiliency of results is doing a tolerance analysis, in which you flip one or two cases to see if it changes the overall pattern. So, in this case, what if you run the numbers as if Cole or Strasburg signed with a bad team? I bet your percentages would be so completely different. This means that your analysis rests on one or two cases, rendering just about any result unreliable.
It seems like this would be the case when analyzing any small sample size. In my opinion, this means we should take the results with a grain of salt, but not that we should discard them entirely. Ben is appropriately not making any sweeping conclusions based on the data he looked at.
Ben,
This is a good write up, perhaps you can find more answers by investigating teams that made FA acquisitions in relation to their previous and new payrolls as well as the previous and new WAR offered at the position filled or even the team WAR. For instance, I might not want to include a big FA worth 6.0 WAR if he is replacing a guy with 5.8 who just came off the payroll. I don’t believe that should be included in these measurements per say.
The same goes with the payroll side of things, maybe more importantly even. I wouldn’t say a team is going for it if they sign $30 million in player contracts following a season where $25 million just came off the books via trade of contract expiration, etc. Sure they added a big FA, but only $5 million worth of salary which is likely a minimal difference in team WAR as well, thus they are more or less maintaining things rather than “going for it”.
One thing that has struck me was the first two graphs and in particular the “Good Free Agent Graph”. Both of these seem to indicate that the free agent classes for 2017-2019 represented a bad run of free agent classes. 2017 was the worst free agent class in the sample by quite a bit, with 2018 and 2019 both being below average as well. Additionally, 2015 was the second worse free agent class in the sample.
It would seem that, perhaps, teams are not investing in free agents not because of collusion but because the available free agents have been so bad over the last few years. This could certainly be a result of the current collective bargaining system preventing players from reaching free agency while they are still good or it could be that teams disproportionately release/allow worse players to reach free agency or some other combination of factors, including extending their good players before free agency.
I think the combination of the aging curve and reluctance to spend on aging players are major factors as well
Serious props for publishing a piece where you found no-effect. We need more examples of when we fail to reject the null hypothesis!
Isn’t it possible that good free agents tend to get signed first? That’s what people were complaining about last year: the market was slow until Harper, and Machado signed. Or that was the theory at least. And probably the better players go to teams that at least seem like they will be good soon, so probably not awful teams. Those are also probably the teams willing to spend.
Great work, Ben!
I think the next step is here looking at what these free agents were PROJECTED to do when they signed, not what they had just accomplished. Free agents, after all, are signed for what they are supposed to do, not what they’ve done.
Also, I wonder about the distinction between re-signing and truly new teams (2 of 3 the top 3 being “new teams” this year). For the future!
I am still looking into how to do this, but I don’t have projections going back far enough. Working on building this kind of database for myself, though.
Maybe a question for Meg, but were you surprised by ESPN’s propaganda piece advocating on behalf of the owners’ perspective? None of the facts are incorrect but I was taken back by how blatantly they useD statistics in every way possible to highlight how much is being spent and that the teams are doing all they can.
https://www.espn.com/mlb/story/_/id/28330072/red-sox-owe-team-record-134m-luxury-tax-yanks-cubs-sent-bills
I believe that’s an AP wire article, not ESPN
How is that a propaganda piece? I can’t see that it’s pushing any kind of agenda or biased perspective. It’s just reporting facts about spending. Did you mean to link to something else?
Good stuff. One question…..would the conclusion be the same if you looked at the number of players signed, rather than total WAR? Cole has more WAR than any two signings by the Brewers, yet the Brewers have signed more FAs than the Yankees…….the analysis, to me, looks like it has the “average” problem. You seem to have framed the question as who signed the most WAR, not who signed the most players……
I did consider it! In fact, that is initially how I wanted to do the study. The problem is, there are a lot of free agents, like 12000 free agents in the last 20 years (per retrosheet). The majority of them are minor league and such, but even affer filtering those out, there were a bunch of random people to muck up the analysis. Also, I’m not sure whether the Brewers signing five backups should count five times as much as Cole. In the end, I decided that looking at the amount of talent each team was adding was what I wanted to know, not whether the Orioles signed some lottery tickets. They are different questions, though, and may have different answers.
thanks!
“…winning percentage, an elegant metric for a more civilized age”
LOL. I love this line.
Another great write-up by you, Ben. I love your work.
I think you need to include NET change by team type. Most of the elite players came out of playoff teams this year which wasn’t true last year.
To clarify the reason I think this is important is that teams which lose large amounts of talent are probably going to replace it. And that Houston not replacing talent lost is as significant as the Yankees adding talent.
I wonder how many players moved from a non 2019 playoff team to a 2019 playoff team or vice versa as compared to other years.
I like this idea! Gonna look into this soon.