Baseball Case Study: Performance of Best Free Agents One Year Before and One Year After Signing FA Contract

I’m a big Seattle Mariners fan. The team has seen recent success after 20+ years of missing the playoffs, primarily via drafting and trading for players rather than adding through free agency. As such, the team has just the 18th-highest payroll at $134 million but it has outperformed big spenders like the New York Mets ($344 million) and New York Yankees ($279 million) that acquires pricy free agents in the offseason (Source: https://www.spotrac.com/mlb/payroll/).

I and other Mariner fans have been frustrated with the team not spending more on free agents, so I decided to do data analysis to see if this is the right move. My study is fairly simple. The scope is the production of each of the top 10 free agents from 2010 to 2021 by bWAR production over the past three seasons in the season directly prior to signing a new contract and the production of the same players in the season directly after signing a new contract.

Let’s break down what this all means. First: bWAR is a catch-all baseball statistic that roughly sums up how good a given MLB player is compared to a replacement level player. The higher the bWAR, the better the player. It has some flaws but is useful here to summarize a player’s worth.

Second: I limited the scope of players to be simply the top 10 players by bWAR produced over the past three years because it is a simple way to illustrate the best players available in a given free agent class. This is not to say the free agents available with lower bWAR over the past three years aren’t important–I wanted to look at the best available by bWAR because they tend to be the priciest to acquire and thus least likeliest for the Mariners to sign.

Third: I limited the year range to be between 2010 and 2021 because 2010 is about when all baseball front offices completely adopted SABRmetrics and new-school baseball data analytics such as bWAR. I ended it with the 2021 free agent class because the 2023 season has not concluded and I did not feel confident in projecting the production of the free agent class of 2022.

Fourth: for the 2020 season shortened by Covid-19, I did project the production of players for a full 162 game season based on the numbers they put up in the 60 game season. I want to be open about this since the 2020 numbers used in this study are not necessarily reflective of reality.

With all that out of the way, let’s start by comparing the bWAR of the best free agents in the season prior to signing a new contract to the bWAR of the best free agents in the season after signing a new contract.

Just at a quick glance, you can see that the best free agents produce less the year after they sign a big contract. There’s only one player who put up a negative bWAR before becoming a free agent (Ervin Santana in 2018) while eight players put up negative bWAR after signing a new contract. For context, that means teams who signed a player worth negative bWAR would’ve been better off setting the money spent on fire rather than signing that player. The 110 free agents in this study put up a combined 396 bWAR in seasons prior to signing a new contract, then put up a combined 282.8 bWAR in seasons after. An average post-contract player would be expected to lose just over 1 bWAR in value in the season after signing their contract–talk about depreciation!

Of course, not all ballplayers are equal, and you can’t expect consistent year-to-year production from most players. But surely the players signed to the largest contracts are able to replicate or even surpass the production they accrued in the years prior, right? Let’s look at performance for value next.

For the most part, the more money spent on a player, the better they do perform. AAV is short for “Average Annual Value” and is a player’s yearly salary based on their contract. For instance, the best production-for-money-spent contract on here is Hyun Jin Ryu’s 2020 season where he put up 7.7 bWAR for just $20 million. On the other hand, Madison Bumgarner’s 2020 was the worst value as he delivered a gruesome -1.3 bWAR for $17 million. Ouch!

All told, $1.8663 billions of dollars was spent for 282.8 bWAR. That means that 1 bWAR costs around $6.6 million, but that number will continue to rise as salaries for players continue to increase.

In conclusion, while a big name free agent is expected to depreciate in production after signing a new contract, it is still worth signing big name free agents to improve your baseball team. A league average MLB starter puts up between 1 to 2 bWAR a year. Based on this sample size, a big name free agent puts up 2.96 bWAR on average. That is most likely an improvement. That said, adding a big name free agent comes with an average annual salary of $17 million, and, again, that price will only continue to go up. So while winning as many games as possible is theoretically the goal of every baseball team, it is still a business, and paying top dollar for low production is always a risk that’ll scare off low-budget teams.

I am happy that this case study reaffirmed my belief that the Seattle Mariners should pursue more big name free agents like when they got Robbie Ray, Robinson Cano, and Nelson Cruz since this exact moment is when they could add a great player to get them a championship. Please sign the checks, John Stanton.

Appendix:

Baseball Reference was used for the free agent tracker and player statistical data.

Spotrac was used for contract data.

R Studio Desktop was used to generate the visualizations in this case study.

Batter data is in this spreadsheet.

Pitcher data is in this spreadsheet.