Notice: Trying to get property 'display_name' of non-object in /var/www/html/wp-content/plugins/wordpress-seo/src/generators/schema/article.php on line 52
keyboard_arrow_uptop

Most of our writers didn't enter the world sporting an @baseballprospectus.com address; with a few exceptions, they started out somewhere else. In an effort to up your reading pleasure while tipping our caps to some of the most illuminating work being done elsewhere on the internet, we'll be yielding the stage once a week to the best and brightest baseball writers, researchers, and thinkers from outside of the BP umbrella. If you'd like to nominate a guest contributor (including yourself), please drop us a line.

Jonathan Judge got a degree in piano performance, but then thought better of it and became a trial lawyer instead. His hobbies include the Brewers, proper roster construction, and thinking about BABIP (which are not all necessarily related). Follow him on Twitter at @bachlaw.

We’ve gotten fairly good at valuing many aspects of major league player performance, commonly through variants of wins above replacement (WARP or WAR). We’ve also been able to show a compelling connection between the sum of a team’s individual player “wins” and actual team wins in the regular-season standings. What we haven’t done sufficiently, in my opinion, is to appreciate the way that the best teams construct their rosters to maintain those accumulated player wins over time. In other words, it would be nice to have a way to measure how successful teams develop and maintain a “core” of winning players.

Quantifying and understanding the quality of a team’s core is important. As we enter the thick of another baseball offseason, the state of a team’s core dictates whether it can rely primarily on players who are already on the active roster to grow and sustain performance, or whether the team instead needs to raid its farm system—such as it may be—or turn to pricey/volatile free agents.

To be sure, many writers express opinions about teams having a winning “core.” But these opinions tend to be ad hoc, and they also tend to focus on individual players without fairly considering the strength of any roster as a whole. Most importantly, since they’re not based on objective criteria, they do not allow apples-to-apples comparisons of the overall core strength between teams.

It is past time that we devised a way to summarize mathematically the extent to which each team, in a given season, is deriving its success from “core” players.

My solution is called “Core Wins,” and it answers what I think is a three-part question. First, we have to decide what it means to make a “core contribution” to a roster, and how to measure, objectively, the contributions made by different types of players. Second, using the recent achievements of the Tampa Bay Rays as a reference, we’ll decide what levels of core player contributions are significant. Finally, we’ll rank all 30 major league clubs by the strength of their player cores as they proceed through this offseason.

Defining Core Contributions
It goes without saying that a “core” contributor is one who provides positive value to the team. That’s the easy part.

But what transforms a merely “good” or “highly useful” player into a “core” contributor involves two additional factors: the amount of control the player’s team has over him, and the age at which the player is currently playing.

Control is the more important factor. A player under team control for multiple years has more “core” value to his team than a departing free agent. Team control can arise either through baseball’s collective bargaining agreement, which generally provides six years of team control over newly-promoted players, or free agency, by which players with more than six years of roster experience sign contracts with teams of their choosing. Once either type of player has been added to the roster, the source of the team’s control is basically irrelevant, and I do not distinguish between them here.

Age is important as well. Younger players get injured less, will probably improve over time, and are cheaper. Older players, by contrast, play fewer games in a season, trend downward in their performance, and are more expensive. But since the main value of youth is in the guaranteed control it provides, and we are already considering control, age should be weighed less heavily than control in evaluating a player’s “core” value, and that’s what I did here.

So, we have three components: (1) Player Performance, (2) Team Control, and (3) Player Age. Here is how I combined them:

Player Performance
Using the metric of Wins Above Replacement Player (WARP), as currently calculated by Baseball Prospectus, I reviewed the performance of every player during the 2013 baseball season who made a positive overall contribution to his major league club. For pitchers, their batting and pitching WARP were summed. Only players posting positive total WARP figures were considered.

Team Control
Player control numbers were drawn primarily from Cot’s Contracts, and cross-checked with Baseball Reference, other sources, and common sense as needed. Control years were weighted the same, 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.

To create a weighting factor for team control, I made two years of control—defined by me as being under contract for the 2013 and 2014 seasons—the baseline. That baseline became the denominator in a fraction I call the Control Index, with the numerator being the actual years of control the team had remaining over a player. So, a player in the last year of his contract would have a Control Index of 0.5, and a player subject to four years of team control would have a Control Index of 2.0. For a variety of reasons, I did not consider the impact of more than five years of team control, so the maximum Control Index that could be applied to a player’s 2013 performance was 2.5.

Player Age Component
To account for player age, I used the generally-accepted peak age of 27 as a numerator. My Age Index was comprised of this peak age divided by each player’s so-called baseball age (their age on July 1, 2013) during the 2013 season. So, a player with a baseball age of 27 would have an Age Index of 1.0. In 2013, the youngest positive contributors in baseball were Manny Machado and Jose Fernandez. At a baseball age of 20, both players had an Age Index of 1.35. The oldest player I found was Andy Pettitte at 41. His Age Index was 0.66. Although baseball players do not approach and decline from their peak age at a uniform rate, I didn’t feel that a more targeted approach would produce a significantly better result. (I am willing to share my data with anyone interested in showing otherwise).

For each positive roster contributor in 2013, I multiplied their total WARP times their Age Index times their Control Index. The result of that calculation for each player is the number of Core Wins he produced during the season. I then totaled the Core Wins for each player on each team to allow us to compare teams to each other.

Defining a Strong Roster Core: the Approach of the Tampa Bay Rays
In a pilot study, I did a core win analysis for the 2009–2012 seasons of the Tampa Bay Rays, the New York Mets, and the Oakland Athletics. The Rays were of particular interest to me, as their approach over the last several years seems to epitomize a focus on building a strong roster core, as I have defined it, specifically: (1) the acquisition of talented younger players, (2) the signing of the best of those players to team-friendly deals, (3) then further extending or, alternatively, trading those players for new controlled talent. From the 2009 through the 2012 seasons, the Rays averaged 90 team wins (and added 92 more in 2013). And they’ve done it on a shoestring budget.

What does the Core Wins system tell us about how the Rays built their winning rosters? I noticed three things: First, in the aggregate, the Rays racked large numbers of Core Wins each year from 2009 through 2012. Second, the Rays consistently feature a substantial number of what I will call Core Players—players who generated five or more Core Wins during the season. This means that the Rays were getting both breadth and depth from the roster. Third, the Rays averaged at least two pitchers each year among those Core Players.

So, with thanks to the Rays, there you have my formula for what constitutes a strong roster core: (1) a large number of Core Wins; (2) a large number of Core Players (players with five Core Wins or more); and (3) having at least two and preferably more pitchers within that realm of Core Players, to provide stability and a well-rounded roster.

For the time being, I’ve decided to weigh each attribute equally in the Core Roster Rankings I’ve assigned to each team. Having a good core requires star players, including star players who can pitch, and ideally it is paired with enough controllable depth to fill out the rest of the team effectively. It’s certainly possible to succeed with only one or two out of the three, but it isn’t preferable.

Ranking the Major League Rosters
As mentioned above, I ran a Core Wins analysis for every team in baseball. I then ranked them in each of the three categories: (1) the total number of Core Players; (2) the total number of Core Players who were pitchers; and (3) Core Win Differential (the difference between a team’s aggregate Core Wins and underlying WARP, thereby isolating the value of additional player “wins” from “core”-type players). I then averaged each team’s ranking in each category to provide my overall rankings of the best roster cores in baseball.

Figure 1: Best Roster Cores, Ranked

Team

Core Players

Core Pitchers

Pos. CW / Pos. WARP Differential

Core Roster Strength

Cardinals

8

4

58

1

Braves

8

2

47

2

Rockies

6

2

40

3

Indians

6

1

41

4

Rangers

6

2

31

5

Nationals

5

1

41

6

Angels

4

1

48*

7

Pirates

5

1

38

8

Tigers

7

5

24

9

Dodgers

6

3

25

10

Giants

4

1

37

11

Reds

6

1

30

11

Mets

4

2

31

11

Rays

4

1

35

14

Brewers

5

0

37

15

Dbacks

3

1

32

16

Marlins

3

1

32

16

Phillies

3

2

23

18

Mariners

3

1

28

19

White Sox

2

2

26

20

Athletics

3

0

33

20

Orioles

4

0

29

22

Blue Jays

4

0

25

23

Royals

3

0

30

24

Padres

2

1

18

25

Red Sox

3

0

18

26

Cubs

3

0

15

27

Twins

2

0

23

28

Astros

2

0

22

29

Yankees

0

0

-3

30

MEDIAN

4

1

31

It probably doesn’t surprise you that the Cardinals tied for the highest number of Core Players, or that the Tigers have the best pitching core in baseball, or that the quality of the Cardinals’ overall core generally blew everyone else away. Nor is it terribly surprising to learn that the 2013 Yankees were so dilapidated that they were the one team to actually generate negative core roster quality during the 2013 season. And some of you might have guessed that the runners-up for the pennant in both leagues—the Tigers and Dodgers—have plenty of stars, but a few too many scrubs, as reflected in their low Core Win Differentials.

On the other hand, it may surprise you to see the World Series Champion Red Sox ranking only 26th out of 30 teams in the Core Roster Strength; or that the Rockies ranked third in baseball in core contributions last year; or that the Rays’ roster magic may finally be starting to wear off.

Two Contrasting Cores: the Cardinals and the Red Sox
To show how we got to Figure 1, let’s look at the two teams that met in the World Series, and that brought very different types of rosters to that contest.

We’ll begin with the Cardinals, who through a combination of good drafting, shrewd trades, and some luck have (according to my method, anyway) compiled the best roster core in baseball. Here is an excerpt of the primary players of interest from their chart:

Figure 2: The 2013 Cardinals (excerpt)

Name

Age

WARP

Control Years

Control Index

Age Index

Core Wins

Matt Carpenter

27

7.32

5

2.50

1.00

18

Adam Wainwright

31

5.06

5

2.50

0.87

11

Yadier Molina

30

4.34

5

2.50

0.90

10

Lance Lynn

26

3.55

5

2.50

1.04

9

Matt Holliday

33

3.32

5

2.50

0.82

7

Trevor Rosenthal

23

2.25

5

2.50

1.17

7

Shelby Miller

22

2.02

5

2.50

1.23

6

Allen Craig

28

2.39

5

2.50

0.96

6

Pete Kozma

25

1.59

5

2.50

1.08

4

Jon Jay

28

1.96

4

2.00

0.96

4

Matt Adams

24

1.19

5

2.50

1.13

3

Daniel Descalso

26

1.42

4

2.00

1.04

3

Michael Wacha

22

0.87

5

2.50

1.23

3

Kevin Siegrist

23

0.89

5

2.50

1.17

3

Joe Kelly

25

0.89

5

2.50

1.08

2

Shane Robinson

28

0.61

5

2.50

0.96

1

Carlos Beltran

36

3.13

1

0.50

0.75

1

The table shows you my inputs (Age, WARP, Control Years), my Indices (Control and Age), and finally the calculated Core Wins figure for each player. Core Players who are also pitchers have their names italicized in the Name column.

The chart hopefully makes clear how well this Cardinals core performed in 2013. Of their top eight contributors, seven were under club control for five years or more. That adds up to a lot of Core Wins, and helps explain why the Cardinals were able to essentially dominate all three areas of core roster strength. Only Carlos Beltran—their sixth-highest contributor in 2013 by WARP—is a notable departing asset. Because he is both a departing and an aged player, his Control and Age Indices discount an otherwise solid contribution from being anything close to a core one.

The Red Sox represent the flip side. Their roster generated more WARP than any other club in the 2013 regular season. However, a great deal of that production is heading out the door, and the aging remnants should struggle to replace it from within. Here is an excerpt from their calculation chart:

Figure 3: The 2013 Red Sox (excerpt)

Name

Age

WARP

Control Years

Control Index

Age Index

Core Wins

Dustin Pedroia

29

4.53

5

2.50

0.93

11

Shane Victorino

32

5.27

3

1.50

0.84

7

Daniel Nava

30

2.87

5

2.50

0.90

6

Jose Iglesias

23

1.51

5

2.50

1.17

4

Clay Buchholz

28

1.77

5

2.50

0.96

4

Felix Doubront

25

1.41

5

2.50

1.08

4

David Ortiz

37

4.88

2

1.00

0.73

4

Mike Carp

27

1.68

4

2.00

1.00

3

Jon Lester

29

2.69

2

1.00

0.93

3

Will Middlebrooks

24

0.86

5

2.50

1.13

2

John Lackey

34

1.75

3

1.50

0.79

2

Jacoby Ellsbury

29

4.39

1

0.50

0.93

2

Junichi Tazawa

27

1

4

2.00

1.00

2

Brandon Workman

24

0.7

5

2.50

1.13

2

Xander Bogaerts

20

0.52

5

2.50

1.35

2

Jarrod Saltalamacchia

28

3.38

1

0.50

0.96

2

Jonny Gomes

32

1.71

2

1.00

0.84

1

Stephen Drew

30

2.89

1

0.50

0.90

1

Mike Napoli

31

2.73

1

0.50

0.87

1

Last season may have been “do or die” year for the Red Sox. They registered only three Core Players, and none of them was a pitcher. Of their top 10 contributors in 2013, five of them are on the open market. The Core Wins formula discounts the contributions of the departing free agents accordingly, and the Red Sox now face a predicament heading into 2014. With a top-rated farm system and substantial financial resources, they have more ability to replenish than most, but they have a lot of work ahead of them.

The Role of Individual Performances
Before we wrap up, let’s talk about some of the extraordinary individual performances that we saw across the league in 2013, because those performances can be cause for both praise and concern.

Here are the top individual Core Win totals in the 2013 season:

Figure 4: Best Core Players, 2013 Season

Name

Age

WARP

Control Years

Control Index

Age Index

Core Wins

Mike Trout

21

10.44

5

2.50

1.29

34

Manny Machado

20

6.01

5

2.50

1.35

20

Paul Goldschmidt

25

7.49

5

2.50

1.08

20

Matt Carpenter

27

7.32

5

2.50

1.00

18

Jean Segura

23

5.55

5

2.50

1.17

16

Andrelton Simmons

23

5.41

5

2.50

1.17

16

Joey Votto

29

6.73

5

2.50

0.93

16

Andrew McCutchen

26

6.03

5

2.50

1.04

16

Evan Longoria

27

6.23

5

2.50

1.00

16

Josh Donaldson

27

6.19

5

2.50

1.00

15

Congratulations to the teams who invested in these players: by my calculation, these are your ultimate core contributors. These players are under maximum team control and still at or below their likely prime years of production.

To the rosters with fairly robust cores, such as the Cardinals and the Pirates, Matt Carpenter and Andrew McCutchen provide stable, superstar production to complement an otherwise solid collection of players.

But for teams like the Angels, Orioles, and Athletics, the remarkable production of Mike Trout, Manny Machado, and Josh Donaldson is as much a warning as it is an achievement. This is because the remarkable accomplishments of those players cannot be allowed to mask underlying deficiencies in the cores of those rosters. Both the Orioles and the Athletics rank in the bottom half of the league in core roster quality, and Trout singlehandedly comprises one half of the Angels’s entire Core Win Differential, a fact that caused me to put an asterisk next to that figure in Figure 1 above.

Without these well-earned but nonetheless outlying performances, the challenges facing these teams would be even starker. If they truly plan to benefit from the “core” peaks of these stars, they have some work to do in the very near future. And if they are not realistically going to benefit in the near term from these performances, they ought to be asking whether they would benefit more from trades to make their cores stronger as a whole down the road.

Conclusion
The 2013 Red Sox proved that you don’t need a young core to win the World Series, and having a strong core certainly does not guarantee success. Furthermore, a core-worthy performance in one season does not guarantee a core contribution over the long term. Just as in real life, the Core Wins metric discounts players each year, as they get older and presumably closer to free agency. This both raises expectations for individual players and makes any core difficult to sustain over time.

But when analyzing the present day, Core Wins does tell you which teams have the luxury of seeking selective upgrades, as opposed to those that will be relying on the aspirations of new arrivals. In the meantime, as you weigh the “best” signings or long-term direction of a particular club, take into account the current strength of their core. As much as anything, that should tell you where the club’s near-term focus ought to lie.

Thank you for reading

This is a free article. If you enjoyed it, consider subscribing to Baseball Prospectus. Subscriptions support ongoing public baseball research and analysis in an increasingly proprietary environment.

Subscribe now
You need to be logged in to comment. Login or Subscribe
bobbygrace
11/26
This is a fascinating study and a compelling method. I hope that BP will invite you back to present any follow-up work that you do.

In response to the last paragraph: The first sentence seems more apt than the second. Core Wins appears to be an imperfect measure of where teams' near-term focus ought to lie, in part because a handful of teams (chiefly the Yankees) have much more money to throw around than the others and in part because other teams (notably the Blue Jays) have a lot invested in a core that isn't particularly young, such that they should be aiming to win now even if their Core Wins score wouldn't suggest as much.

Accordingly, one could take the Core Wins score and adjust it to create a "Win-Now Index" by factoring in how much money a team has committed, as well as how much money a team has left to throw around. A Win-Now Index might also factor in the strength of a team's farm system to account for the possibility of upgrading via trade. (If a "farm system" score would be a viable possibility, one could also use it to create a "Core Strength" index that focused more directly on a team's long-term viability, as indicated by the youth and "controllability" of the players in its system.)
walrus0909
11/26
Counterpoint: Core players (by any definition) are rarely made available and, as such, are super expensive. Teams may find it more cost effective to sign a bunch of contributing players to modest, short-term deals, shoring up the bottom of their rosters, rather than use their limited resources on a "stars-and-scrubs" type approach that leaves them vulnerable to injury or underperformance.

From a recent FanGraphs article on the Athletics' return to the top of the AL West: "These A’s teams are bottom heavy, as they’ve gotten production from nearly every spot on the roster, rather than having a small core of stars do the bulk of the heavy lifting."

http://www.fangraphs.com/blogs/the-as-are-moneyballing-again/
bobbygrace
11/26
Good point. The 2013 Red Sox had an analogous construction: they had a few clear stars and weren't exactly an inexpensive team, but when they spent on free agents prior to the season they opted to spread out the wealth rather than pick up two or three marquee players.

Of course, the Core Wins theory evinced here is more for the small- and medium-market teams than for the big spenders. Few teams have the luxury of spending $150M+ on free agents in a single offseason. So, the A's are a better case study for those who would advocate a strength-in-numbers approach.
Ogremace
11/28
It's worth noting that this metric isn't really a "stars and scrubs" type of descriptor. Obviously the very productive players will top out the Core Players list, but because of the way its calculated less robust production is scaled by team control and age. So a strong core could be constructed by a young cadre of not-necessarily-overwhelming performers. I'm sure some math could be worked out to describe this more concretely, but the upshot is that it's not simply a metric of performance.

I find this to be a very interesting and pleasantly straightforward analysis. It would be intersting to apply this calculation to a period of (past) years and determine correlations between various performance metrics (statistical performance, league rankings, titles etc.). Hopefully others will take up your research and expand its applications as it deserves.
bachlaw
11/29
Thanks very much.

Yes, I'd like to do that. Going back 3 or 4 years times 30 teams for each year would give a very nice sample for some trustworthy correlations. It's just very time-consuming to do the inputting. But, I do plan to get to it and will look forward to what we find.
harrypav
11/28
Do you have a ranking of the top 4 year players?
Kongos
11/29
Most interesting thing I've read on BP in ages. Thanks!
ericmvan
11/30
I just wrote a pretty extensive critique, with a suggested revised methodology, here:

http://forum.soxprospects.com/post/56332

I think the general idea here is fabulous. Unfortunately, WARP is currently a very bad metric (especially for pitchers), so that adds a lot of noise. And when you have an idea like this, you always want to try to create a model that *empirically predicts the thing it claims to predict*, rather than guessing at weighting factors.