The Best Bargains of 2015
There’s a lot of talk about market inefficiency in the long aisles of the baseball analysis superstore: which teams find value where others don’t, and, conversely, which teams see value that maybe isn’t there anymore (or even in the first place). For small market teams, finding inefficiencies is a matter of successful survival, and for large market teams, it’s a way of adding something extra to the x-factor that works: money.
Whatever the case may be, it’s part of our job to measure how teams are faring in the efficiency department, and we do that generally by looking at how much teams are spending in relation to what they’re actually getting, production-wise. Today, we’re not exactly going to go into specific strategies, like what the most recent Billy Beane magic wand looks like, but rather see which position players are projected to provide the most amount of production (WAR) for the least amount of money ($).
To do that, we’re going to split players into two groups: those making the league minimum, and those who aren’t. This is mainly so we don’t skew the data too much with extremely talented young players who haven’t yet reached arbitration. Those with more service time and who have hit free agency get their own group.
First, we’ll look at players who have hit free agency or arbitration. My fellow FanGraphs scribe Craig, who has been working on some great pieces about payroll and projections, laid some ground work and supplied the contract data for 2015. I’ve combined the contract specifics for all teams with WAR projections and calculated the cost per projected win.
It’s not perfect, and neither are any 2015 projections. We know WAR is sensitive to defensive performance in a given year — it’s meant to be the center of a player’s possible range of production, and we’re going to keep that in mind as we move forward. However, this is meant to give us an idea of which players are great bargains, and it will do that nicely.
I’ve filtered the top 30 position players by cost per projected win and have presented them below. I’m going to supply these in both graph and table form. We begin with the post-arbitration crowd, and their salary vs. expected WAR for 2015:
And now we present the same data in a table format, with the all-important cost per win field added:
| Name | Team | Position | 2015 Salary | Proj. WAR | Cost/Win |
|---|---|---|---|---|---|
| Yan Gomes | Cleveland | C | $1,083,334 | 3.9 | $277,778 |
| Starling Marte | Pittsburgh | LF | $1,333,333 | 3.7 | $360,360 |
| Salvador Perez | Kansas City | C | $1,750,000 | 3.9 | $448,718 |
| Anthony Rendon | Washington | 3B | 2,700,000 | 4.4 | $613,636 |
| Mike Trout | Los Angeles (AL) | CF | $6,083,333 | 9.6 | $633,681 |
| Jonathan Lucroy | Milwaukee | C | $3,400,000 | 5.3 | $641,509 |
| Bryce Harper | Washington | LF | $2,500,000 | 3.7 | $675,676 |
| Jarrod Dyson | Kansas City | CF | $1,225,000 | 1.8 | $680,556 |
| Jose Altuve | Houston | 2B | $2,687,500 | 3.9 | $689,103 |
| Paul Goldschmidt | Arizona | 1B | $3,100,000 | 4.4 | $704,545 |
| Rene Rivera | Tampa Bay | C | $1,200,000 | 1.7 | $705,882 |
| Brett Lawrie | Oakland | 3B | $1,925,000 | 2.5 | $770,000 |
| Josh Donaldson | Toronto | 3B | $4,300,000 | 5.4 | $796,296 |
| Lorenzo Cain | Kansas City | CF | $2,725,000 | 3.3 | $825,758 |
| Hank Conger | Houston | C | $1,075,000 | 1.3 | $826,923 |
| Devin Mesoraco | Cincinnati | C | $2,525,000 | 2.9 | $870,690 |
| Craig Gentry | Oakland | OF | $1,600,000 | 1.8 | $888,889 |
| Andrelton Simmons | Atlanta | SS | $3,142,857 | 3.5 | $897,959 |
| Michael McKenry | Colorado | C | $1,088,000 | 1.2 | $906,667 |
| Martin Maldonado | Milwaukee | C | $825,000 | 0.9 | $916,667 |
| Josh Harrison | Pittsburgh | 3B-SS | $2,800,000 | 3.0 | $933,333 |
| Lonnie Chisenhall | Cleveland | 3B | $2,250,000 | 2.4 | $937,500 |
| Peter Bourjos | St. Louis | CF | $1,650,000 | 1.7 | $970,588 |
| Collin Cowgill | Los Angeles (AL) | CF-RF | $995,000 | 1.0 | $995,000 |
| Todd Frazier | Cincinnati | 3B | $3,750,000 | 3.7 | $1,013,514 |
| Desmond Jennings | Tampa Bay | CF | $3,100,000 | 2.9 | $1,068,966 |
| Francisco Cervelli | Pittsburgh | C | $987,500 | 0.9 | $1,097,222 |
| Kyle Seager | Seattle | 3B | $4,500,000 | 4.1 | $1,097,561 |
| Matt Carpenter | St. Louis | 3B | $3,750,000 | 3.4 | $1,102,941 |
| Giancarlo Stanton | Miami | RF | $6,500,000 | 5.7 | $1,140,351 |
A few things jump out right away: there are a lot of catchers, which can point to the sometimes difficult nature of projecting defense at the catcher position. However, I don’t think it’s too much of a surprise to see our friend Yan Gomes leading the charge: he’s growing into one of the best offensive catchers in the game, he just signed a team friendly, back-loaded contract, and he had an outstanding 2013 defensive campaign.
We see a lot of speedy outfielders with great defense and base running skills, and the table also highlights the lack of low-cost, high-production first basemen. This was highlighted yesterday: right now, first basemen are getting paid a lot of money league-wide. I’m inclined to think this is because we’re in a time when many veteran, franchise first basemen are in the middle of their contracts, pushing the cost for that position skyward, but that needs more research and less speculation.
Now let’s move onto the young guns: the pre-arbitration position players. As a primer, let me say this: pre-arbitration salary plans differ by club. Some give raises per year based on number of plate appearances, some do service time, and all generally keep their scheme under wraps. The important thing to know is that any difference in pre-arbitration salaries are really small. Because those salaries aren’t always disclosed, and for the simple sake of ease, I’ve set the salaries for all of these players at the league minimum for 2015: $507,500. Also because of this, I’ve charted this one a little differently — because we know everyone’s salary (or close to it), I’ve put cost per win in place of salary. Here we go:
And now also in table form:
| Name | Team | Position | 2015 Salary | Proj. WAR | Cost/Win |
|---|---|---|---|---|---|
| Manny Machado | Baltimore | 3B | $507,500 | 4.5 | $112,777.78 |
| Christian Yelich | Miami | LF | $507,500 | 4.0 | $126,875.00 |
| Joc Pederson | Los Angeles (NL) | OF | $507,500 | 3.4 | $149,264.71 |
| Mookie Betts | Boston | 2B | $507,500 | 3.4 | $149,264.71 |
| Nolan Arenado | Colorado | 3B | $507,500 | 3.4 | $149,264.71 |
| A.J. Pollock | Arizona | CF | $507,500 | 3.2 | $158,593.75 |
| Adam Eaton | Chicago (AL) | CF | $507,500 | 3.2 | $158,593.75 |
| Gregory Polanco | Pittsburgh | OF | $507,500 | 3.2 | $158,593.75 |
| Billy Hamilton | Cincinnati | CF | $507,500 | 3.1 | $163,709.68 |
| George Springer | Houston | RF | $507,500 | 3.1 | $163,709.68 |
| Juan Lagares | New York (NL) | CF | $507,500 | 3.0 | $169,166.67 |
| Kole Calhoun | Los Angeles (AL) | RF | $507,500 | 3.0 | $169,166.67 |
| Brian Dozier | Minnesota | 2B | $507,500 | 2.7 | $187,962.96 |
| Kevin Kiermaier | Tampa Bay | CF | $507,500 | 2.7 | $187,962.96 |
| Yasmani Grandal | Los Angeles (NL) | C | $507,500 | 2.7 | $187,962.96 |
| Kolten Wong | St. Louis | 2B | $507,500 | 2.6 | $195,192.31 |
| Chris Owings | Arizona | SS | $507,500 | 2.5 | $203,000.00 |
| Marcus Semien | Oakland | INF | $507,500 | 2.5 | $203,000.00 |
| Xander Bogaerts | Boston | SS | $507,500 | 2.5 | $203,000.00 |
| Arismendy Alcantara | Chicago (NL) | SS | $507,500 | 2.4 | $211,458.33 |
| Marcell Ozuna | Miami | OF | $507,500 | 2.4 | $211,458.33 |
| Scott Van Slyke | Los Angeles (NL) | OF-1B | $507,500 | 2.4 | $211,458.33 |
| Chris Taylor | Seattle | SS | $507,500 | 2.3 | $220,652.17 |
| Derek Norris | San Diego | C | $507,500 | 2.3 | $220,652.17 |
| Ender Inciarte | Arizona | OF | $507,500 | 2.3 | $220,652.17 |
| Jean Segura | Milwaukee | SS | $507,500 | 2.3 | $220,652.17 |
| Josmil Pinto | Minnesota | C | $507,500 | 2.3 | $220,652.17 |
| Brad Miller | Seattle | SS | $507,500 | 2.2 | $230,681.82 |
| Eugenio Suarez | Cincinnati | SS-2B | $507,500 | 2.2 | $230,681.82 |
| Javier Baez | Chicago (NL) | SS | $507,500 | 2.2 | $230,681.82 |
These are the names we know, the ones we hope for, the players that the perennial next year is all about. You can argue with some of the minutiae of the projections if you want to, but there’s no arguing that this list is a who’s-who of great prospects, as it should be. While there might be some surprises on the first list, this second one holds no illusions.
Finally, a point that should be taken into account with this research is that it pertains to 2015 only – many of these very reasonable salaries (for the first group) in 2015 are part of back-loaded contracts that will explode in the next few years. Yan Gomes is one of them: he’s due for a raise of $1.5 million in 2016 and $2 million in 2017. That’s still a bargain for a great all-around catcher, but it’s less of a bargain than it is this year.
As we see less young, talented free agents hitting the market in the current era, more tact and strategy will be needed from teams on when and how to extend their young players. Commit too early in the hopes of locking a player up, and you could be stuck with paying someone who might not pan out; commit too late, and you’re not getting value for your money or another teams swoops in during free agency. Given the first group, the current strategy seems to be extend, backload, and hope to trade before the players become too much of a payroll liability. We’re seeing how that strategy is working out with huge, aging free agent contracts. Many teams can afford those deals; many can’t.
For some teams, finding this value is about survival. For the others, it’s just icing on top of a very expensive cake.
Thanks to Sean Dolinar for the graphic templates.
Owen Watson writes for FanGraphs and The Hardball Times. Follow him on Twitter @ohwatson.


Wouldn’t best bargains be better measured by excess value (Wins Projected-Wins paid for) than cost per win? The second group would be unchanged but there would be significant shuffling in the first group.
yeah, my immediate thought was this after not seeing Cutch on the list. Surplus value is another interesting way to look at this and you can get rid of guys like Cervelli and not bias your sample to low cost players.
100% agreed. the values are all so low ($1m and lower), that in theory a GM would likely be more concerned with maximizing total WAR than maximizing $/WAR.
It obviously passes the smell test, as you’d prefer Stanton over Gomes and Colin Cowgill should not be on the list…
Thanks for the feedback, all – will include this dimension in my companion piece on pitching tomorrow.
What about using AAV [perhaps adjusted to PV] instead of strictly 2015 salary? Stanton only gets $6.5M this year, but he wouldn’t have agreed to that on it’s own [probably would have gotten $10-12M in arbitration]. So his 2015 is artificially low because of the 0ther 13 years on the contract.
I guess I should have read all of the comments before posting 🙂
I don’t know… wouldn’t YOU prefer an investment where you can turn $1 into $2, rather than one that will turn $10000 into $19000? Who’s with me?! 😉
I get the premise- these guys are good values for their production, but how is this a market inefficiency that can be exploited? The pre-arb value guys are all a product of a good farm system as their salary is pretty much pre-determined and I think every team realizes the value of good, young, cheap players. And the post-arb guys are those signed to reasonable contracts. I think every team is is at least trying to get good value for the money they spend.
Where would my namesake, Mr Stroman, have been on the second chart if he hadn’t been cursed?
ZiPS has not updated, shows a projection of 3 wins, which puts him right with Lagares and Calhoun. I tend to think he would’ve pitched more than the 175 innings ZiPS projected, though.
Pitchers are coming tomorrow! These are just position players.
I wonder if this would look drastically different if you used AAV of a contract instead of 2015 salary. Obviously, Trout and Stanton would go away. Would there be players on the back end of contracts, who played cheap earlier in their careers, show up?
How is Abreu not included in the list above?
Uhh… because math? He’s projected to 4.1 WAR (via ZiPS) and will make $7 million, which is about $1,700,000 per win, which falls outside the range of the chart.
Maybe he meant Bobby.
It would be fascinating to see a scatter plot of years of service time vs. cost-per-win, perhaps colored by position.
Yasiel Puig seems to be missing from the top chart. Zips has him at 5.2 WAR, Cots has his salary at $4.5 million, which means his cost/win is about $865,000
He was just outside the top 30 (he’s 34th) – his salary for 2015 is actually $6,214,000, and with a 5.2 WAR, that puts him at $1,195,055 per win. I see that salary figure here at Cots: https://spreadsheets.google.com/pub?key=tBbMgiEHXYczpjt0I7dajQQ&output=html
Ah, I see. That uses the prorated signing bonus ($12 million over 7 years) whereas I used base salary.
Why did you go with the bar graph over a scatterplot? What does it communicate better than the scatter plot besides “magnitude of salary”, that makes it worth putting two different measurements on the same axis?
name of player?
at first i thought someone was “learning” you with a pithy reply… or did you respond to your own unnecessary and insulting comment with one of the many possible logical answers?
Visual display of information can mean a lot and I was having trouble figuring out how to relate what I see on the bar chart to what makes a bargain. There is a tradeoff in choosing any one way to communicate the information at hand. I am asking what the motive was for choosing the bar graph because they are best used for magnitude comparisons of the same unit of measure, and the metric of interest in the article is a ratio of two different units of measure.
As in, to compare bargains with a bar chart, you need to compare two units of data from a first entry to construct a first ratio, do the same for a second entry to construct a second ratio, then compare those ratios. With, say, a scatter plot, you need to compare two positions. The visual comparison involved with constructing a ratio is pretty much ingrained in the position of the data point of a scatter plot (especially with a clever choice of scale), whereas in the bar chart the ratio (i.e., the metric of interest) is not immediately recognizable.
I think a scatter plot is an example of a good way to indicate information about ratios, and am wondering why a bar graph was chosen. I’m not out to insult the author as suggested but to learn more about how people think about presenting their information.
Actually, the name of the player is a large reason for a bar graph. A scatter plot would have too many point to annotate every player. The bar graph facilitates comparison between two different players. I can tell Trout is a better deal than Stanton this year or that Donaldson is a better deal than Seager with the bar chart.
If the analysis was focused on calling out one or two players from many (think best bargain among catchers) , then a scatter plot would work well. The player’s data point would be separated from the pack. In the case of this data set you would be highlighting a quadrant of players.
But to your point a scatter plot would be a good way to introduce the subset of bargain players relative to the league as a whole.
Give me Anthony Rizzo at $5 million for this season.
ditto to Rizzo. Where is Carlos Gomez? Is this cause they were not a free agent or arbitrated?
Carlos Gomez
Zips: 5.0 fWAR
Cot’s: $8M
$8M/5.0 = 1.6 $/win
—
Anthony Rizzo
Zips: 4.2 fWAR
Cot’s: $5M
$5M/4.2 = 1.2 $/win
Kevin Cash announced Kiermaier will only play CF this year, and Jennings will be moved to left, when KK is in CF. How does that affect both of them?
The lack of first basemen makes sense. Look at the thirty starting first basemen and you see a lot of players who played another position when they were young and cheap.
I think the main reason for the lack of first basemen is the impact of defensive WAR. If so, that suggests two possibilities; either defensive WAR is faulty or baseball management don’t value defense nearly as much as they should.
Doesn’t this just continue to confirm that the replacement level for catchers that Fangraphs uses is not being reflected by the league? i.e., fWAR overvalues catchers?