Does Your Team Have a Winning Core? Profiling Sustainable Roster Construction

Thanks to an atrocious month of May, the 2013 Milwaukee Brewers were abruptly transformed from a fringe contender into a rebuilding baseball club.

Most people agree that the Brewers need to build a new core, but what does that mean? Many teams have young players in the midst of an above-average season, but that doesn’t necessarily translate to sustainable success for the roster as a whole. And the opinions expressed about so-called core players are usually subjective and not expressed in a way that allows direct comparisons between teams.

We could really use a metric to compare the rosters of teams who are developing potentially sustainable talent with those who aren’t. My effort to do this is called Core Wins, which summarizes the extent to which a team’s success is being driven from players most likely to constitute core talent, as opposed to players on their way out the door, probably in decline, or both.

To do this, we need define what it means to be a core player, and specifically the factors by which we evaluate a core player’s respective contributions to the team.

The Core Player

In my view, core players do three things: (1) contribute significantly to their team’s success, (2) do so while under extended team control, and (3) do so at or before they reach their peak ages of likely productivity. Each of those attributes needs to be mathematically summarized to reduce these contributions to a measurable value.

The first factor is the easiest: a core player is expected to contribute, and to do so above what could be found in an entry-level minor-league call-up. A major league player’s ability to do so over the course of a season is commonly summarized in some version of the wins above replacement (WAR) metric, which attempts to combine the player’s batting, fielding, and if applicable, pitching contributions. A counting statistic also fits our needs best, since we are looking for aggregate contributions over the course of a single season. So, we’ll use WAR, as calculated by Fangraphs (fWAR).

The second factor, team control, is more complicated. Player control comes in two primary forms: (1) players under club control due to the terms of baseball’s collective bargaining agreement, and (2) players who have signed freely-negotiated contracts. The collective bargaining agreement keeps players under club control for at least six major league years. Free agent contracts range from one-year stop-gaps to those lasting a decade or longer. Most ballclubs are a collection of young players under sustained club control, long-term (and typically expensive) free agents, and stopgap players on value contracts. But teams with a sustainable core should be drawing significant production from players who will actually be around in future years. If too much production is coming from departing or declining players, the club is asking for trouble.

The third factor — player age — is less significant, but still important. Younger players are cheaper than older players, and thus easier to afford and keep around. Younger players are less frequently injured, meaning they will be in the lineup more often. Younger players who have not yet reached their peak production age will also probably continue to improve, whereas players beyond their peak age will probably decline.

However, age can be overemphasized. The primary advantage of youth— extended club control — is already being considered. Moreover, mature players signed to long-term contracts tend to be some of the most valuable players in the game — Joey Votto, Felix Hernandez, and their peers. And while prospects are important, most ballclubs would strongly prefer Joey Votto over a 22-year old prospect who may, but probably won’t, someday turn into Joey Votto. So while age matters, it is not as important as control.

So to summarize: we need to weigh player value, but do it in a way that primarily emphasizes team control while still placing some value on a player’s age.


Player Contributions

All WAR figures were drawn from Fangraphs. The figures for batting fWAR (which incorporates fielding) and pitching fWAR were combined into one spreadsheet for each team year. When a player generated values for both batting (plus fielding) and pitching WAR, those values were summed, including the effect of any negative values. Once a net value was obtained for all players on a team roster for the year, all zero or net negative WAR values were disregarded.

Player Control Index

Player control numbers were drawn primarily from Cot’s Contracts, and cross-checked with Baseball Reference, other sources, and common sense as needed. Cot’s provides individual player contract data from 2009 onward, so only data from 2009 through 2012 was used. Control years were weighted identically, regardless of whether they arose from the CBA or a free agent contract. A player subject to a club option was considered to be under club control for that year. The author’s best estimate of remaining club control was necessary in a few cases when contract details were unclear, but not surprisingly, most of those players were fringe contributors that would not constitute core talent anyway.

A player was assigned one control year if his contract expired after the current season, two control years if his contract expired after the following season, and so on. For practical reasons — including the frequent shuffling from the minors experienced by young players, and the oft-diminishing returns of the longest contracts — the maximum number of control years considered for a player was 5. A Control Index was then calculated for each player in each roster year, with the number of control years as numerator, and an assigned denominator of 2 — for the minimum years that would constitute extended organizational control. So, for example, a player with an expiring contract would have a Control Index of 0.5 (1 season left divided by 2), and a typical player in their final pre-arbitration year would have a Control Index of 2.0 (4 seasons of control divided by 2). The maximum Control Index is 2.5.

Age Index

A player’s “baseball age” — their age on July 1 of a given season — was drawn from Fangraphs. An Age Index was then calculated for each player using an assigned value for a typical peak performance age as the numerator and the player’s baseball age for each season as the denominator. There has been some debate on the overall peak performance age for ball players, but, taking a strong hint from one of my reviewers, I used 27. To give some sense of the value range, the Age Index in 2012 for Mike Trout would have been 1.35 (27/20) and for Livan Hernandez would have been 0.73 (27/37).

Determining Core Win Value

In my formula, Core Win value is a weighting exercise. To calculate a player’s Core Win value to a roster, I multiplied the player’s net fWAR for each season by the Control Index and the Age Index. The Control Index has a greater range (0.5 to 2.5) and thus a greater potential weight than the Age Index, which seems appropriate for the reasons stated above. The combined effect of these indices means young prospects that produce at a level of 2 fWAR or higher are weighted the most heavily. This makes sense: players who promptly adjust to the difficulty of the major leagues, yet still have years of probable improvement ahead of them, all while under extended team control, are those most likely to constitute a sustainable core of talent for the ballclub.


Now that we have a formula for Core Win Value, we need to decide what it means to have a winning core. That cut-off is ultimately in the eye of the beholder, but I looked to the gold standard: the Tampa Bay Rays. The Rays are widely acclaimed for their ability to acquire and maintain control of young talent, often through early buy-outs of free agent years, combined with club options that retain team flexibility. This has been particularly true over the years covered by this study: 2009 through 2012.

To provide some contrast with the Rays, we will also consider the roster construction during that same time period of the New York Mets and the Oakland Athletics.

The Gold Standard: The Rays

Not surprisingly, the Core Wins formula likes the Rays very much. Indeed, three characteristics of the Rays between 2009 and 2012 suggest a working definition of a team with a strong, sustainable core: (1) the Rays consistently feature five or more players producing a Core Win Value of 5 or higher per season, which is my working definition of a “Core Player”; (2) they have accomplished this feat in multiple consecutive years (all four years I studied, in fact) and (3) at least two of these Core Players were usually pitchers.

Let’s start with 2009. For ease of viewing, in each of these tables, I’ve bolded wins figures for potential Core Players (five or more Core Wins). I’ve also italicized the names of pitchers who cross the Core Wins threshold, to distinguish them from position players.

2009 Tampa Bay Rays

Name fWAR Age Control Years Control Index Age Index Core Wins
Evan Longoria 7.5 23 5 2.50 1.17 22
Ben Zobrist 8.5 28 5 2.50 0.96 20
James Shields 3.5 27 5 2.50 1.00 9
Matt Garza 2.9 25 5 2.50 1.08 8
Jason Bartlett 5.3 29 3 1.50 0.93 7
Carl Crawford 5.6 27 2 1.00 1.00 6
B.J. Upton 2.1 24 4 2.00 1.13 5
David Price 1.3 23 5 2.50 1.17 4

In 2009, the Rays won 84 games, featuring seven players that delivered 5 Core Wins or more. This depth, plus MVP-level performances from Evan Longoria and Ben Zobrist, prepared the Rays for the eventual departure of Carl Crawford, whose dwindling team control was removing him from the team’s core. Note that the team’s two best pitchers in 2009, James Shields and Matt Garza, were both under team control for 5 more years. David Price generated only 1.3 fWAR in 2009, and thus barely missed the Core Wins cut, but he was on the upswing.

2010 Tampa Bay Rays

Name fWAR Age Control Years Control Index Age Index Core Wins
Evan Longoria 7.6 24 5 2.50 1.13 21
David Price 3.9 24 5 2.50 1.13 11
Ben Zobrist 3.7 29 5 2.50 0.93 9
B.J. Upton 3.8 25 3 1.50 1.08 6
John Jaso 2.3 26 5 2.50 1.04 6
Sean Rodriguez 2.1 25 5 2.50 1.08 6
Matt Joyce 1.7 25 5 2.50 1.08 5
James Shields 1.7 28 5 2.50 0.96 4
Carl Crawford 7.4 28 1 0.50 0.96 4
Matt Garza 1.5 26 4 2.00 1.04 3

In 2010, the Rays maintained 7 players at a Core Win level of 5 or more, culminating in 96 team wins and a first-place finish in the AL East. Only one pitcher (David Price) made the Core Win cut-off of 5 this time, but James Shields just missed it. Matt Garza regressed a bit (and was promptly traded to the Cubs for more prospects, without any negative effect). Carl Crawford, despite an MVP-level year of 7.4 fWAR, is discounted out of the team core by the Core Wins formula, due to his team control ending that year.

2011 Tampa Bay Rays

Name fWAR Age Control Years Control Index Age Index Core Wins
Ben Zobrist 6.2 30 5 2.50 0.90 14
Evan Longoria 6.2 25 4 2.00 1.08 13
David Price 4.3 25 5 2.50 1.08 12
Matt Joyce 3.5 26 5 2.50 1.04 9
James Shields 4.4 29 4 2.00 0.93 8
Desmond Jennings 2.3 24 5 2.50 1.13 6

2011 featured more of the same. Carl Crawford was gone, but the Rays did not miss him, as the formula anticipated. Six Rays met the Core Win threshold, two of them pitchers (Price, Shields). Superstar contributions by Zobrist and Longoria, combined with ascending contributions from four others — including Price and Shields — resulted in a highly-successful season from Tampa Bay’s controlled talent, and others. The Rays won 91 games and made a wild-card playoff appearance.

2012 Tampa Bay Rays

Name fWAR Age Control Years Control Index Age Index Core Wins
Ben Zobrist 5.8 31 4 2.00 0.87 10
David Price 4.8 26 4 2.00 1.04 10
Desmond Jennings 3.3 25 5 2.50 1.08 9
Matt Moore 2.4 23 5 2.50 1.17 7
Evan Longoria 2.5 26 5 2.50 1.04 6
Alex Cobb 2.0 24 5 2.50 1.13 6
Jake McGee 2.0 25 5 2.50 1.08 5
James Shields 3.9 30 3 1.50 0.90 5

By 2012, the Rays had developed an astonishing eight players that crossed our Core Win threshold. An incredible five of these players — over half the team’s core, under our formula — were starting pitchers with at least four years of team control remaining. This means that the Rays’ entire starting rotation was under long-term control. Despite a hamstring injury that kept him out for over three months, Evan Longoria still contributed 2.5 fWAR to the effort, and his new contract provided the team with the long-term control to keep him in the team’s core. The 2012 Rays won 90 games: not enough for even a wildcard in the American League that year, but a terrific season nonetheless.

Before the 2013 season, the Rays dealt James Shields to Kansas City for the bat of Wil Meyers and other prospects. As of the publication of this article, Fangraphs projects them to win 93 games in 2013, on a payroll of only $62 million. In sum, the Rays have been, and continue to be, the prototypical team that demonstrates what it means to have a sustainable core of controlled talent.

By Stark Contrast, the New York Mets

The Mets have been bad for years, and the Core Wins formula identifies major flaws in roster construction as a possible culprit.

2009 New York Mets

Name WAR Age Control Years Control Index Age Index Core Wins
David Wright 3.4 26 5 2.50 1.04 9
Johan Santana 3.2 30 5 2.50 0.90 7
Angel Pagan 2.8 27 4 2.00 1.00 6

Dreadful: there is no other way to describe the 2009 Mets. That year, the Mets spent $140 million for 70 team wins, generating only three Core Players under our formula. Even those players gave only ok performances. From a Core Wins perspective, this roster was terrible. One of the three players to meet the Core Wins threshold, and the only starting pitcher — Johan Santana — is heading past his probable prime.

2010 New York Mets

Name WAR Age Control Years Control Index Age Index Core Wins
Ike Davis 3.1 23 5 2.50 1.17 9
Johan Santana 3.6 31 5 2.50 0.87 8
Angel Pagan 5.1 28 3 1.50 0.96 7
David Wright 3.5 27 4 2.00 1.00 7
Jon Niese 2.1 23 5 2.50 1.17 6
Mike Pelfrey 2.2 26 4 2.00 1.04 5

The results for the Mets weren’t much better in 2010 — 79 wins — but their roster at least improved. Six players made Core Player-type contributions, and two of those players were starting pitchers. If these performances proved to be sustainable over multiple years, or at least into 2011, the Mets had some reason for optimism.

2011 New York Mets

Name WAR Age Control Years Control Index Age Index Core Wins
Daniel Murphy 2.8 26 5 2.50 1.04 7
Jon Niese 2.1 24 5 2.50 1.13 6
Ruben Tejada 1.6 21 5 2.50 1.29 5
Ike Davis 1.3 24 5 2.50 1.13 4
Jose Reyes 5.8 28 1 0.50 0.96 3
David Wright 1.7 28 3 1.50 0.96 3

But it didn’t work out. In 2011, the Mets were right back to a pathetic three Core Player performances, with only one starting pitcher among them. In fact, the Mets’s strongest core performance in 2011 came from 2.8-win Daniel Murphy. Not good. Ike Davis promptly regressed out of the core, David Wright fought injuries, and Johann Santana didn’t play all year, which is why Core Wins discounts the value of aging players. Although Jose Reyes provided a superstar WAR of 5.8 and a batting title, as a departing free agent, that performance provided no ongoing value to the team, and the Core Wins formula discounts it accordingly. It all amounted to 77 wins, and low expectations for the following season.

2012 New York Mets

Name WAR Age Control Years Control Index Age Index Core Wins
Jon Niese 2.7 25 5 2.50 1.08 7
David Wright 7.4 29 2 1.00 0.93 7
Ruben Tejada 1.7 22 5 2.50 1.23 5
Matt Harvey 1.5 23 5 2.50 1.17 4
R.A. Dickey 4.4 37 2 1.00 0.73 3

Validating this expectation, the 2012 Mets did even worse, winning only 74 games. Only three players could pass the Core Wins threshold, and one of their best players — R.A. Dickey — could not even quality as a Core Player, despite 4.4 fWAR. The Core Wins formula discounts the going-forward value of 37-year-old performances, and Dickey’s 2013 performance with the Blue Jays has validated that skepticism.

But, the Mets get enough bad news, so let’s focus on some positive aspects. In 2012, David Wright performed at an MVP level. And while the Mets had only four Core Win players in 2011, two of them are starting pitchers, which is an important positive from our study of the Rays. In fact, one starter, Jon Niese, was signed to an early long-term contract a very Rays thing to do, putting a competent starter under extended team control. Matt Harvey also looks to be a championship-caliber ace, and remains under maximum team control.

So far, 2013 is not being kind to the Mets either — Fangraphs currently projects them to finish with 76 wins — but there are hints that things may soon be looking up, particularly if their farm system can continue to develop strong rotation talent, as many project that it will.

Trending in the Right Direction: The Oakland Athletics

Finally, let’s conclude with what turns out to be a Goldilocks example: the team that like the Mets, tried and failed to improve their core, but stuck with it and seems to have gotten the hang of it lately: the Oakland Athletics.

2009 Oakland Athletics

Name WAR Age Control Years Control Index Age Index Core Wins
Brett Anderson 3.6 21 5 2.50 1.29 12
Ryan Sweeney 3.9 24 5 2.50 1.13 11
Rajai Davis 3.7 28 5 2.50 0.96 9
Kurt Suzuki 3.1 25 5 2.50 1.08 8
Dallas Braden 2.7 25 5 2.50 1.08 7
Andrew Bailey 2.3 25 5 2.50 1.08 6

In terms of roster-building, the 2009 Athletics took a fairly solid approach: they ended up with six potential Core Players, and three of them are starting pitchers. All these players offered at least five years of team control. However, the 2009 Athletics also underscore that just because your wins are coming from the right place does not mean you are getting enough of them. The best performance in this group is still only 3.9 fWAR — good, not great. The 2009 Athletics won only 74 games, although at least they didn’t have to pay Mets prices to get there.

2010 Oakland Athletics

Name WAR Age Control Years Control Index Age Index Core Wins
Daric Barton 4.8 24 5 2.50 1.13 14
Cliff Pennington 3.4 26 5 2.50 1.04 9
Gio Gonzalez 2.9 24 5 2.50 1.13 8
Brett Anderson 2.4 22 5 2.50 1.23 7
Dallas Braden 3.3 26 4 2.00 1.04 7
Trevor Cahill 1.6 22 5 2.50 1.23 5

In 2010, the Athletics were better. Leveraging some of the previous year’s young talent, they ended up 81-81. There were six core-type player performances, and four of them pitchers: ordinarily, a good thing. But notably, there was not a significant amount of improvement from 2009’s core contributors. In fact, the strongest core contributors in 2010, Daric Barton and Cliff Pennington, were marginal contributors the year before, raising the possibility of fluke performances. And, only two core performances came from position players, which didn’t leave much room for error going forward in the scoring department. So, the 2010 Athletics showed hints of a developing core, but a fragile one.

2011 Oakland Athletics

Name WAR Age Control Years Control Index Age Index Core Wins
Gio Gonzalez 3.2 25 5 2.50 1.08 9
Jemile Weeks 1.7 24 5 2.50 1.13 5
Trevor Cahill 2 23 4 2.00 1.17 5

And indeed it was. The Athletics rotation was devastated by injuries in 2011: Dallas Braden needed shoulder surgery, and Brett Anderson needed Tommy John surgery. That would be a tough blow for any team, but particularly for Oakland, which did not have much behind them. What was left of the rotation (and roster) collapsed to three core-type players. The two core bats of consequence in 2010, Daric Barton and Cliff Pennington, immediately regressed and revealed themselves to be one-year wonders. The only developing bat remaining was an average, but unspectacular debut by Jemile Weeks, whose own performance later proved unsustainable.

Although two out of the three core players were starting pitchers, there was little to support it. Brandon McCarthy actually had a very good year (4.5 fWAR), but since he was completing a 1-year-deal at the time, he offered the A’s no core value.

Things looked bleak. Fortunately, the A’s stuck to their guns and kept developing young talent. Then, 2012 happened.

2012 Oakland Athletics

Name WAR Age Control Years Control Index Age Index Core Wins
Josh Reddick 4.5 25 5 2.50 1.08 12
Jarrod Parker 3.4 23 5 2.50 1.17 10
Tommy Milone 2.8 25 5 2.50 1.08 8
Yoenis Cespedes 2.9 26 4 2.00 1.04 6
Brandon Moss 2.3 28 5 2.50 0.96 6
Sean Doolittle 1.6 25 5 2.50 1.08 4

2012 found the Athletics again having restocked their core, this time with a balance of bats and pitching talent. Five core players are represented, and their values are not all projection, either: Josh Reddick produced 4.5 fWAR, Jarrod Parker generated 3.4 fWAR, and two other controlled players produced close to 3 fWAR. Two core players are starting pitchers. Furthermore, in 2012, the A’s finally enjoyed a little luck. They outplayed their Pythagorean expectation by a few wins, got 2+ win performances from non-core starters on short-term deals — Brandon McCarthy and Bartolo Colon — and ended up with 94 wins and an AL West title, on top of what appeared to be developing core.

If you thought that the Athletics were finally getting the hang of this roster-building thing, you may be right. The Athletics have spent much of 2013 on top of the AL West, and Fangraphs currently projects them to finish with 91 wins — on a budget of $62 million. A very Rays-like experience all around, which corresponds with quality roster construction.


The Core Wins metric profiles the extent to which team performances are being delivered by so-called Core Players, and also tracks the progression of players in and out of the club’s core over time. Even herculean performances by impending free agents (see Carl Crawford, 2010) tend to wash out of the metric, while young players who initially impress, but fail to sustain (see Ike Davis, 2011) also fall out of the measured core, despite their built-in advantages of youth and team control. As such, Core Wins strikes me as useful and if nothing else, an improvement over the prevailing practice of eyeballing the roster and cherry-picking performances by younger players.

Because it is based on WAR (a counting statistic), Core Wins is primarily backward-looking. But, the general method can also be used prospectively. For example, if you input projections from your preferred player projection system, you could forecast the extent to which your team is likely to get future contributions from sustainable sources — a useful thing to know when deciding between trades, farm system call-ups, or free agent signings. Similarly, if you want to focus on particular positions of concern — (third base, starting rotation) — or skill sets (batter OBP, pitcher FIP) — you can adjust the Age Index to account for the peak performance ages corresponding with those particular positions or skills. Those analyses can be retrospective or prospective.

Of course, superior roster construction does not guarantee superior performance, as the Oakland A’s can attest. Previously healthy players can be felled by injury, and promising talents too often fail to sustain early achievements. But in general, developing Core Players makes good sense, and certainly seems to be delivering results for the league’s most efficient ballclubs. So if your favorite team seems incapable of stacking success, you might check to see how good of a job the front office has been doing in generating Core Wins.

Special thanks to Paul Noonan and Tom Tango, who both offered helpful comments on the general direction of this article. All errors are entirely my own, including some table pasting errors in the original version. Thanks to Andrew Yuskaitis for pointing those out. They have now been corrected.

Jonathan Judge has a degree in piano performance, but is now a product liability lawyer. He has written for Disciples of Uecker and Baseball Prospectus. Follow him on Twitter @bachlaw.

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10 years ago

I just wanted to compliment you on your work. Your methodology is excellent, and the article reads very well. I am just a little confused on the exact formula you are using to produce the final Core Wins value. Based on the article, it sounds like you are using fWAR*(Control Index + Age Index), but that formula would obviously be too high. Could tell me the correct formula please?

10 years ago

Really nicely done. I’m curious, why the emphasis on core starting pitchers?

10 years ago

Jonathan, thanks for setting me straight on the formula.

10 years ago

I like the direction of this, but I think it seems to place a lot of weight on single-year results. Why not just use a standard estimator for future performance (e.g., ZIPS), convert to WAR, use empirical age adjustments (e.g.,, and then dot-product them over the contract duration? That would probably smooth out some of the blips a bit.

The other issue is that it doesn’t seem to account for salary particularly. Implicit in having a good core is that they are controlling costs. Unless your “net” WAR means (Performance WAR – Salary/($/WAR)), you are not accounting for that. Intuitively, having a lot of surplus value seems like what I imagine in a core at least.

Without these adjustments, I’d estimate that the Ryan Howard extension looks like starting 2010 with a great core player (4.4 WAR 2009 season, Age~30, 5+ years of control) rather than a huge albatross. The same might apply to a number of other very misguided deals.

10 years ago
Reply to  Z

But again, very interesting work. Not trying to sling mud, just a couple of thoughts that occurred to me.

Andrew Yuskaitis
10 years ago

I really like this formula. Just one thing I noticed. While describing your age index, you said you used 27 as the numerator. But a quick look at some of your math shows you used 29 as the numerator. See Jason Bartlett and Carl Crawford in the 2009 Rays. Why the difference?

Matt L
10 years ago

Could I see your calculations for the 2010-2012 Atlanta Braves?