Salary predictions for Free Agents - Does a team's winning % and payroll matter?

by Jeff Zimmerman (TucsonRoyal) on Jan 13, 2009 12:20 PM EST Comment 24 comments

Question: How does a players ability and the payroll, performance and home team discount of the team he signs with determine how much of a salary he will be offered/accept?

Why I asked the question: I was wonder the amount that smaller teams have to pay more than better (more payroll and/or higher winning percentage) teams to get good talent to come to their team.

Analysis: I decided to look at the 2007-2008 free agent class when doing this initial study (will expand as time permits and suggestions are taken into account) The variables for most of the data was pretty strait forward.

Free Agents – I used the ESPN list of free agents, their salary and if they switched teams (home team discount). Only players that were given Major league contracts and that had a VORP from the previous season were used.
Total team salaries – CBSSportsline.com. I looked at the final 2008 value.
VORP – Baseballprospectus.com list both VORP for pitchers and hitters. The players VORP from the previous season were only used. Most free agent decisions are based on what the ball player has done recently.

Note: As you can tell the data was from several different sources, so if there happens to be any inconsistencies or transposition errors, please let me know.

After running a multiple regression for a predicted salary against payroll, VORP, wins over .500 and home team discount I got the following values:

Factor	Salary Amount
Base Salary	108,500
Extra paid per win over 500	12,000
Hometown Discount	-108,000
1 point of VORP above league average	209,000
Amount paid per 10,000,000 in total payroll	233,398

r-squared: 0.622

Standard Deviation of: 3,000,000

This wasn't what I expected. It seems that teams that are winning actually pay more for the same level of talent as teams that win less and those with higher payrolls over pay (i.e. Yankees). This is probably do to the bidding wars that teams get into for the top talent. Also, the home discount of ~1 million is much more of factor than the team's winning percentage that signs the player.

For example let's look at Mark Loretta's contract of 2.75 million. He starts with a base salary of 108,500 and almost gives it all up with his hometown discount of -108,000 since he stayed with Houston. His VORP of 10.5 leads to a salary of 2,000,000. While Houston being 8 games below .500 means they paid 95,000 less, but their payroll of 89 million means he should of another 2.1 million more. His estimated salary would be about 3.2 million or 450,000 less than he is currently making.

As I am a huge fan of charts, here are some of more of the results:

Top Ten Overpaid Players:

Name	Team Signed by	Amount over paid
Andruw Jones	LA Dodgers	13,933,330
Torii Hunter	LA Angels	6,542,104
Mariano Rivera	NY Yankees	6,132,745
Francisco Cordero	Cincinnati	5,884,827
Jose Guillen	Kansas City	4,969,959
Eric Gagne	Milwaukee	4,956,344
Jason Jennings	Texas	4,132,468
Alex Rodriguez	NY Yankees	3,760,672
Andy Pettitte	NY Yankees	3,755,589
Kip Wells	Colorado	3,552,833

Top Ten Underpaid Players:

Name	Team Signed by	Amount under paid
Jorge Posada	NY Yankees	5,919,700
Chad Durbin	Philadelphia	4,702,272
LaTroy Hawkins	NY Yankees	4,687,160
Shawn Chacon	Houston	4,367,667
Sean Casey	Boston	4,280,449
David Riske	Milwaukee	3,521,124
Josh Fogg	Cincinnati	3,356,606
Matt Wise	NY Mets	3,310,750
Doug Brocail	Houston	2,923,741
Chad Paronto	Houston	2,868,081

Three players that projected to an actual negative salary (they should have paid the team that signed them to play):

Name	Team	Amount owed to team
Emil Brown	Oakland	-740,500
Jason LaRue	St. Louis	-326,622
Jason Jennings	Texas	-132,468

The amount underpaid (+ values) or overpaid (- values) per position

Position	Amount Underpaid/Overpaid
1B	2,673,270
LF	1,063,523
C	617,522
RP	192,965
SP	79,669
3B	-74,550
2B	-256,537
SS	-385,656
RF	-1,898,907
CF	-4,999,808

I looking at expanding the study to include more years. I have the data for 2007-2008 off season, but salaries and Free Agent signings before that are not as readily available. I would also like to incorporate any other factors that might help explain the data. Finally I might remove the games over .500 from the regression analysis since it has very little effect, but I want to wait to see if any other factors are added.

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Comments

What's the split on LHP v RHP?

We have heard for years that there is a shortage of LHPs. Does the data split to reflect that?

by klhoughton on Jan 13, 2009 1:58 PM EST reply actions 0 recs

No, will definately look into that.

I have had feedback to see if the number of years of a contract are longer for smaller teams. The only way they can get the player is to give them another year more than other teams.

by Jeff Zimmerman (TucsonRoyal) on Jan 13, 2009 2:11 PM EST up reply actions 0 recs

Tucson,

Re: teams that win / teams with higher payrolls ‘overpaying,’ this is actually what we should expect, since these teams are higher up on the revenue curve.

Take the Yankees, who are a perfect example of both. For every marginal win, all other things being equal, the Yankees will make more than any other team, since they play in a larger market, etc. So they will obviously be willing to pay more for each marginal win.

The Yankees are also competing for the playoffs every year, and every win between 90-100 is obviously much more valuable than a win between 60-70. So again, they’re willing to pay more per marginal win than teams that may not be in the race.

by shawnhoffman on Jan 13, 2009 11:29 PM EST reply actions 0 recs

Being a Royal's fan is why I was thinking in this manner...

… because I continue to see the Royals to overpay for FA (Guillen, Fansworth and Bloomquist). I guess I was looking for reasons the Royals were spending too much, teams that suck pay a premium to get players, but I was wrong. The Royals management is just clueless.

by Jeff Zimmerman (TucsonRoyal) on Jan 14, 2009 12:03 AM EST up reply actions 0 recs

There's a difference between paying more and overpaying.

Of course they should average the most per marginal win. But when they’re averaging the exact cost of free agent wins, they’re doing something wrong. They should get SOME production from cost-controlled players and then fill in with lots and lots of free agents. Over the past few years, the Red Sox have won about as many games as the Yankees, while spending a lot less money. A $200MM payroll should win about 100 games if properly managed.

Beyond the Boxscore // Calling BJ Upton lazy is lazy.

by Sky Kalkman on Jan 14, 2009 9:13 AM EST up reply actions 0 recs

Actually

$200MM in a league averaging $90MM should win about 95 games, which is about what they’ve done.

Beyond the Boxscore // Calling BJ Upton lazy is lazy.

by Sky Kalkman on Jan 14, 2009 9:14 AM EST up reply actions 0 recs

How fitting that

Emil Brown should have to pay the team to let him play.

by Warden11 on Jan 14, 2009 1:33 PM EST reply actions 0 recs

I am not that far off Tango's salary estimator.

I didn’t want to initially look at others work when doing this salary estimation, but decided to go ahead and check.

Link
Commnet #20

where he states 1 WAR = 2.2 million in Salary and 1WAR = 10.5 runs

2.2 million/10.5 = $209,532 only ~500 dollars off

by Jeff Zimmerman (TucsonRoyal) on Jan 14, 2009 2:03 PM EST reply actions 0 recs

That's quite encouraging.

Beyond the Boxscore // Calling BJ Upton lazy is lazy.

by Sky Kalkman on Jan 14, 2009 9:10 PM EST up reply actions 0 recs

Is foreknowledge of WAR part of the reason you chose to use VORP in your article?

by astrostl on Jan 14, 2009 9:32 PM EST up reply actions 0 recs

I used VORP because ...

…. baseprospectus.com allow to download CSV’s and made the analysis much easier and they had VORP for both pitchers and hitters in one place.

by Jeff Zimmerman (TucsonRoyal) on Jan 14, 2009 11:16 PM EST up reply actions 0 recs

Although it isn't in one place

Fangraphs now as WAR for both pitchers and hitters… although the hitters’ wRAA isn’t adjusted for league average, I don’t think, just MLB average (I could be wrong), and not park adjustments there.

Other than a few tweaks, though, I do think that FanGraphs stuff on this score is considerably better than VORP, and, of course, blows the various iterations of WARP away.

Bringing you more-or-less replacement level analysis and commentary since sometime in 2008.

by devil_fingers on Jan 19, 2009 8:30 PM EST up reply actions 0 recs

I don't have a lot of time and a downloaded CSV is a God send.

Hint, Hint FansGraphs. I also wish FanGraphs have a better search/select data (I want all the Chone projections for the Royals on one page).

by Jeff Zimmerman (TucsonRoyal) on Jan 19, 2009 10:25 PM EST up reply actions 0 recs

I posted a comment like that

but you can still import everything as separate tables then do a join based on player names.

Bringing you more-or-less replacement level analysis and commentary since sometime in 2008.

by devil_fingers on Jan 20, 2009 1:34 PM EST up reply actions 0 recs

Unless I'm missing something

Fangraphs has an “Export to CSV” option. Its right below the Min IP/PA drop down box and above the players/teams list.

Can't get enough of the Oakland A's? Visit Oaktown Awesomer's

by iamawesomer on Jan 21, 2009 12:40 PM EST up reply actions 0 recs

right

I think (like me) TucsonRoyal wants to be able to choose what fields get exported “together,” instead of just having the separated into “batting” “advanced” “win probability” etc., you can choose any fields from any of them to export together for manipulation in Excel/MySQL/whatever

Bringing you more-or-less replacement level analysis and commentary since sometime in 2008.

by devil_fingers on Jan 21, 2009 12:49 PM EST up reply actions 0 recs

My main complaint about the leaderboards is that players aren't broken out by team.

So I can’t export all the data and have Dunn’s performance separated between CIN and ARI. And for fielding, it’s all lumped together, too.

Beyond the Boxscore // Calling BJ Upton lazy is lazy.

by Sky Kalkman on Jan 21, 2009 1:00 PM EST up reply actions 0 recs

+1

I’d also like to be able to “lump” multiple years together in one export for e.g., my next “Little Things” study that will turn up nothing, just like the rist one

Not so much a complaint, of course, but a suggestion. Fangraphs rulez.

Bringing you more-or-less replacement level analysis and commentary since sometime in 2008.

by devil_fingers on Jan 21, 2009 8:00 PM EST up reply actions 0 recs