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April 15, 2014

PECOTA Takes on Prospects

Introduction: I Now Pronounce You Scout and Stat

by Andrew Koo

When I reread Nate Silver’s PECOTA Takes on Prospects series, three themes emerged. One, minor-league statistics are pretty damn good at predicting future performance. Two, so many factors can derail a prediction, particularly for young prospects. Three—which doubles as a disclaimer for this series—I’m not Nate Silver. Apologies in advance.

In the two-year run of his series, Silver, using stats alone, attempted to quantify the future value of prospects with rookie eligibility. He rated each prospect with a metric named UPSIDE and parsed his rankings, explaining why, for example, Dustin Pedroia deserved no. 4 prospect status in 2006, after just 538 (whoa) plate appearances above High-A. Or why UPSIDE projected Alexi Casilla for an excellent five years at shortstop and Troy Tulowitzki for just a decent future. We’ll be doing the same during the next few weeks, aided by Rob McQuown’s revival of Silver’s models.

UPSIDE was conceived to provide a complementary perspective to scouting rankings. It’s not necessarily a better perspective (in fact, it’s not a better perspective)—it’s simply a process that chooses to rely solely on rigorous calculation. Obviously, we should avoid numbers-only approaches when evaluating players—prospects are far more nuanced than their stats and quantifiable attributes. But this extreme approach does provide some benefits. Scouting valuations, while comprehensive, might overweight certain factors. They might say, misadjust on league and level effects. We know the California League is a hitter’s league, but how much of a hitter’s league is it? How much better is the competition in the Eastern League? And consequently, how much do we debit and credit batters and pitchers within our rankings?

This isn’t the fault of scouts, of course. It’s just humanly impossible to consider park, league, and competition-level effects for every player. We know the effects exist, but the adjustments we apply in our head are rarely precise. This is the primary argument for a statistically driven prospect ranking. PECOTA weights such factors objectively, while incorporating additional calculi like position, aging curves, and major-league equivalencies (Davenport translations). PECOTA digests all of these inputs, generates an UPSIDE value for each prospect, and forms a ranked list.

This stat-driven approach not only offers a different perspective, but prompts further questions that may lead to our better understanding of a prospect. The presentation of UPSIDE will be a single figure—which, by the way, is available on the player cards—and when that figure defies the prospect’s scouting diary, we’ll delve into the machinations behind UPSIDE. Is he performing especially well for his age at a high minor-league level? Will his skillset falter against better competition? Does PECOTA project a flat development curve for him?

Models have flaws too. They miss certain attributes. They are emotionless machines that do not discriminate between players (or more accurately, player IDs). This is where scouting comes in: Why, for example, do 185 players rank above Austin Hedges in UPSIDE, who ranks 18th on Jason ParksTop 101? While PECOTA considers age, body type, handedness, past performance, environment, and much more, variables like pitch mix, position flexibility, mental acumen, injuries, and makeup have yet to be incorporated. Models can be powerful, but they’re just simplified versions of reality. We can reference BP’s prospect experts to explain the complexities that PECOTA misses. Together, we hope they’ll provide the most complete view of today’s prospect landscape.

Prospects have upside, but how much UPSIDE?
UPSIDE measures the player’s likelihood of above-average performance while under his parent club’s financial control. For players aged 24 or higher, that’s their next five years. For younger players, it’s the peak projected five-year window (PEAK) through their age-28 season (i.e. whichever is highest between age 20-24, 21-25, etc. to their 24-28 window). Why age 28? As Silver explained in 2007, “This is the real fruit of the unforgiving labor of scouting and development: getting impact performances from players who are still cheap under the reserve clause, or in arbitration.”

With PECOTA as its backbone, UPSIDE calculates these peaks by first finding the prospect’s top 20 Comparable Players. The grittiest calculations arise from here: Each prospect is compared to every baseball player season in our database based on baseball attributes and performance. Each comparison is given a similarity score; we take the 20 highest. The higher a player’s overall Similarity Index, the more confidence we can have in his UPSIDE rating.

Once UPSIDE determines those 20 comparables, it takes the sum of their PEAK above-average WARP values, doubles it, and weights them by similarity (higher similarity score, higher weighting). Basically, UPSIDE determines prospect upside by looking at similar players’ peaks. It disregards below-average performances as they contradict the definition of upside. Here’s Nate again:

The cost of employing a prospect is relatively low, both in terms of financial outlay and opportunity cost (a player can simply be left in the minors if he’s not good enough for MLB), so assigning negative points for a below-average or below-replacement level performance isn’t quite fair.

We’ve modified the definition of UPSIDE from our initial release, which used the sum of PEAK non-negative WARP values. Above-average reflects the UPSIDE definition better than above-replacement: It takes much more skill to clear an average WARP than zero WARP, and that skill would indicate the presence of upside.

With the methodology covered, let’s turn to the rating scale. We interpret UPSIDE by the following chart, borrowed from Nate (and Kevin Goldstein) once more:

Upside Score

Definition

100+

Excellent Prospect. One of the better prospects in baseball. Strong chance of long major league career, perhaps with several All-Star appearances. May have Hall of Fame potential, especially if prospect is young or has a rating of 150 or higher.

50-100

Very Good Prospect. Strong chance of a meaningful major league career, with some legitimate chance at stardom. Best-case outcomes may involve some Hall of Fame potential.

25-50

Good Prospect. Reasonable chance of a meaningful major league career, but only an outside chance at stardom.

10-25

Average Prospect. Some chance of a meaningful major league career, but more likely to end up on the major league fringe. Highly unlikely to make two or more All-Star appearances.

0-10

Marginal Prospect. Very little chance of becoming a major league regular, excluding extreme mitigating circumstances affecting the player’s statistical record.

With that in mind, let’s jump into PECOTA’s Top 100. This ranking is generated solely by PECOTA and its UPSIDE algorithm, with no qualitative adjustments applied. It’s comprised of rookie-eligible players under age 27 and excludes Japanese imports. Jason Parks’ rating of the prospect is listed for comparison, and pitcher rows are shaded.

Rank

Name

Pos

Org

Age

UPSIDE

JP

1

Byron Buxton

CF

MIN

20

219.7

1

2

Oscar Taveras

CF

SLN

22

177.6

3

3

Carlos Correa

SS

HOU

19

141.2

5

4

Joey Gallo

3B

TEX

20

136.7

95

5

Kevin Gausman

RHP

BAL

23

135.6

10

6

Miguel Sano

3B

MIN

21

126.6

14

7

Gregory Polanco

CF

PIT

22

115.7

24

8

Tyler Glasnow

RHP

PIT

20

94.3

42

9

Xander Bogaerts

SS

BOS

21

90.7

2

10

Javier Baez

SS

CHN

21

88.4

4

11

Kevin Plawecki

C

NYN

23

86.8

--

12

Michael Roth

LHP

ANA

24

86.4

--

13

Jackie Bradley

CF

BOS

24

83.5

23

14

Addison Russell

SS

OAK

20

81.6

7

15

Joc Pederson

CF

LAN

22

81.3

50

16

Bruce Rondon

RHP

DET

23

80.6

--

17

Christian Vazquez

C

BOS

23

80

--

18

J.R. Murphy

C

NYA

23

78.9

--

19

Max Stassi

C

HOU

23

76.4

--

20

Marcus Stroman

RHP

TOR

23

74.4

27

21

George Springer

CF

HOU

24

74

20

22

Oscar Hernandez

C

TBA

20

72.8

--

23

Stephen Pryor

RHP

SEA

24

72.4

--

24

Trevor Bauer

RHP

CLE

23

72

--

25

Danny Hultzen

LHP

SEA

24

71.2

--

26

Arodys Vizcaino

RHP

CHN

23

70

--

27

Domingo Santana

RF

HOU

21

68.5

--

28

Charlie Tilson

CF

SLN

21

68.5

--

29

Bubba Starling

CF

KCA

21

66.1

--

30

Alen Hanson

SS

PIT

21

63

--

31

Randal Grichuk

RF

SLN

22

62.8

--

32

Gregory Bird

1B

NYA

21

62.3

--

33

Jason Martin

CF

HOU

18

62

--

34

Pierce Johnson

RHP

CHN

23

61.8

91

35

Corey Seager

SS

LAN

20

61.4

44

36

Josmil Pinto

C

MIN

25

61.3

56

37

Rafael Montero

RHP

NYN

23

60.7

--

38

Zoilo Almonte

LF

NYA

25

60.6

--

39

Yordano Ventura

RHP

KCA

23

60

12

40

John Stilson

RHP

TOR

23

60

--

41

Dixon Llorens

RHP

SLN

21

58.1

--

42

Mallex Smith

CF

SDN

21

57.8

--

43

Erik Johnson

RHP

CHA

24

56

67

44

Dan Vogelbach

1B

CHN

21

55.4

--

45

James Paxton

LHP

SEA

25

54.5

68

46

Jake Marisnick

CF

MIA

23

54.2

--

47

Brian Goodwin

CF

WAS

23

54.1

86

48

Wynston Sawyer

C

BAL

22

53.7

--

49

Manny Banuelos

LHP

NYA

23

53.2

--

50

Matt Davidson

3B

CHA

23

52.7

93

51

Edward Sappelt

CF

MIA

19

52.6

--

52

Shae Simmons

RHP

ATL

23

52.4

--

53

Mookie Betts

2B

BOS

21

52.4

--

54

Burch Smith

RHP

SDN

24

52.1

--

55

Teoscar Hernandez

CF

HOU

21

51.5

--

56

Luke Jackson

RHP

TEX

22

51.5

--

57

Ryan Casteel

C

COL

23

51.2

--

58

C.J. Edwards

RHP

CHN

22

50.7

81

59

Brett Bochy

RHP

SFN

26

50.1

--

60

Jonathan Singleton

1B

HOU

22

49.7

57

61

Charlie Lowell

LHP

MIA

23

49.5

--

62

Maikel Franco

3B

PHI

21

49.5

52

63

Steven Matz

LHP

NYN

23

49.4

--

64

Giovanni Soto

LHP

CLE

23

49.2

--

65

Daniel Corcino

RHP

CIN

23

49.1

--

66

Heath Hembree

RHP

SFN

25

49

--

67

Henry Owens

LHP

BOS

21

48.6

69

68

Jesse Winker

LF

CIN

20

48.5

--

69

Manuel Margot

CF

BOS

19

48

--

70

Brandon Diaz

CF

MIL

19

47.2

--

71

Josh Spence

LHP

MIA

26

47.2

--

72

Nick Wittgren

RHP

MIA

23

46.8

--

73

Josh Bell

RF

PIT

21

46.7

77

74

Johneshwy Fargas

CF

SFN

19

46.7

--

75

Slade Heathcott

CF

NYA

23

46.2

--

76

Mark Montgomery

RHP

NYA

23

46.1

--

77

Jorge Bonifacio

RF

KCA

21

46.1

99

78

Clayton Blackburn

RHP

SFN

21

45.8

--

79

Aderlin Mejia

SS

MIN

22

45.7

--

80

Camden Maron

C

NYN

23

45.5

--

81

Clint Frazier

CF

CLE

19

45.1

36

82

Victor Payano

LHP

TEX

21

44.9

--

83

Shawn Armstrong

RHP

CLE

23

44.8

--

84

Travis d'Arnaud

C

NYN

25

44.7

48

85

Kyle Smith

RHP

HOU

21

43.7

--

86

Miles Head

3B

OAK

23

43.6

--

87

Michael Flores

LHP

ATL

21

43.3

--

88

Samuel Tuivailala

RHP

SLN

21

43.1

--

89

Eduar Lopez

RHP

ANA

19

42.6

--

90

Phillip Ervin

RF

CIN

21

42.5

63

91

Tyler Austin

RF

NYA

22

42.3

--

92

Matt Purke

LHP

WAS

23

42.1

--

93

Harold Ramirez

CF

PIT

19

41.9

--

94

Andrew Susac

C

SFN

24

41.7

--

95

Noah Syndergaard

RHP

NYN

21

41.5

11

96

Jose Ramirez

2B

CLE

21

41.1

--

97

Billy McKinney

CF

OAK

19

41.1

--

98

Nick Castellanos

LF

DET

22

40.9

37

99

Marcus Semien

SS

CHA

23

40.8

--

100

Telvin Nash

1B

HOU

23

40.7

--

Reviewing PECOTA Takes on Prospects, 2006–7

It's been seven years since Nate Silver last wrote this series. Seven years, coincidentally, is the amount of time a team financially controls a player, and UPSIDE, Silver’s prospect metric, attempts to forecast the five-year PEAK within those seven years. Given the time that has passed, we can evaluate the accuracy of UPSIDE from 2006-07.

In his wrap-up of 2006, Silver formed “Team PECOTA,” consisting of the highest-ranking players in his PECOTA Top 50 who did not rank in Baseball America’s top 50. Here they are, with WARP accumulated during their seven-year spans since 2006:

Name

PECOTA Rank (BA)

7-YR MLB time

WARP

Dustin Pedroia

4 (77)

2006-12

19.5

Eduardo Nunez

11 (Unranked)

2010-present

0.9+

Josh Barfield

13 (Unranked)

2006-09

1.0

Ian Kinsler

14 (Unranked)

2006-12

26.5

Corey Hart

16 (Unranked)

2006-12

15.0

Yusmeiro Petit

17 (69)

2006-09, 2012

-0.8

Adam Jones

20 (64)

2006-12

18.5

Donnie Murphy

21 (Unranked)

2007-13

-0.2

Mike Jacobs

22 (Unranked)

2006-12

0.7

Alex Romero

23 (Unranked)

2008-09

-1.5


Hart peaked at 91 on BA’s top 100 in 2002, falling off thereafter. Scouts liked the raw power but feared his long swing, which was already causing high strikeout rates. Nevertheless, .302/.398/.560 with 31 steals in Triple-A—a .302 True Average—impressed PECOTA. In terms of level translations, the gap between Triple-A and the major leagues is small. Pedroia’s high ranking was similarly motivated.

Nunez hit for a .309 TAv in short-season ball during 2005; with few stats to go on, PECOTA fancied the 18-year-old shortstop. He ranked sixth on BA’s top 10 that year too, but after a combined .214/.261/.308 slash across two levels in 2006, he didn’t re-appear in UPSIDE rankings or BA’s top 10. Small-sample, short-season statistics can mislead PECOTA; here, it got Nunez wrong.

Petit pitched very well in Double-A as a 20-year-old, posting walk and strikeout rates of four and 29 percent, respectively, but those have obviously failed to translate to the major leagues. He confused scouts then, too: The numbers were “really quite fantastic,” in Silver’s words, but not the stuff. Despite the reservations, BA ranked him the second-best prospect in the Mets system. We rarely see pitchers who rely on command and deception earn upper-tier prospect status, and BA placed him 77th overall. PECOTA, ranking him 17th, couldn’t make this hedge, not knowing that Petit’s strikeout numbers were a product of command rather than velocity.

We can also review PECOTA’s favorites in its 2007 iteration, compared to Kevin Goldstein’s rankings:

Name

PECOTA Rank (KG)

7-YR MLB time

WARP

Dustin Pedroia

6 (Unranked)

2006-12

19.5

Alexi Casilla

7 (Unranked)

2007-13

0.2

Felix Pie

9 (42)

2007-13

1.6

Chris Iannetta

10 (49)

2007-13

12.2

K. Kouzmanoff

11 (52)

2007-11

4.1

Brent Lillibridge

12 (80)

2008-13

-0.9

Eric Patterson

13 (Unranked)

2007-11

-0.3

Sean Rodriguez

18 (85)

2008-14

3.1+

Kevin Slowey

22 (84)

2007-13

8.8


A much more disappointing group overall—just four of these nine have played in a major-league game this season. Shortstops account for three misses—Casilla, Lillibridge, and Rodriguez. From the same class, Brandon Wood and Reid Brignac joined them as highly rated shortstops on scout lists who just didn’t make it. You can attribute their failure to a number of factors, but the common theme here seems to be lack of major-league power. This wasn’t a huge concern for Silver, as long as the prospect made up for it with contact, batting eye, defense, and speed. However, none of PECOTA’s top-ranked shortstops ended up being outstanding in any such category, and even today, we see very few no-power, average-elsewhere middle infielders—depending on how you view his defense, Alcides Escobar straddled replacement level last year. Without power or a true skill, such prospects constantly live on the major-league fringe, despite playing a premium position.

Tulowitzki, a shortstop prospect who succeeded in that barren ’07 class, was underrated by PECOTA relative to Goldstein’s no. 24 ranking. PECOTA couldn’t pinpoint a “true skill” of Tulowitzki’s or give him bonus points for being a grinder, a word used by both Silver and Goldstein. While PECOTA deemed the above-average contact and speed of the prospects above deserving of high UPSIDE, it wasn’t impressed by Tulowitzki’s then-average power.

Iannetta has the 10th-highest WARP since 2007 among catchers—not bad for a guy who’s never played a full season. As Silver wrote, “I suspect the scouting-based lists are failing to account adequately for his positional value." Scouts dinged Iannetta’s arm and athleticism, but he succeeded thanks to the power and on-base skills he displayed in the minors.

PECOTA knows less than lists informed by scouting info, but it didn’t whiff completely, naming multiple prospects whose skills it liked enough to grant a high UPSIDE rating. The objective of PECOTA/UPSIDE isn’t to replicate or beat the scouting rankings—anyone can espouse the talents of Byron Buxton or Carlos Correa. We’re interested in which prospects the scouting lists leave off entirely, and what PECOTA saw in them based on stats alone. By 2021, PECOTA, acting on incomplete information, will have made more incorrect forecasts, but the prospects it nails may not have been on anyone’s top 100.

PECOTA rates seven prospects as “Excellent” and 52 as “Very Good,” cutting off the fallen Jonathan Singleton as its first “Good” prospect. No surprise up top: Byron Buxton takes the number-one UPSIDE rating, which tends to happen when Mike Trout is your primary comparable. Oscar Taveras follows him, with Colby Rasmus, Wil Myers, and Adam Jones as his first three comparables. As indicated by the rating scale, PECOTA expects long major-league careers out of Buxton and Taveras.

Overall, PECOTA’s top 100 contains 60 position players and 40 pitchers. Of the position players, UPSIDE, as it has in the past, rates shortstops and center fielders quite well. It may actually be overrating them, if we contemplate the trajectory of minor leaguers. PECOTA tends to compare players to others at the same position, but a shortstop in Low-A today might not be a shortstop in the major leagues, because he might not have the range for the position. Nevertheless, teams will keep that potential shortstop at that position in the minors, in hopes that he’ll develop at the position—he has positional upside, after all. That raises the UPSIDE of some shortstops and center fielders, because PECOTA doesn’t necessarily know who will eventually be forced to second base or right field. Attrition at the position happens slowly, and those who make it—the Starlin Castros, the Austin Jacksons—become comparables for current minor leaguers.

PECOTA projects 213 prospects, starting with Singleton, as “Good,” giving them a “reasonable chance at a meaningful major-league career, but only an outside chance at stardom.” Forty-one of them close this top-100 list, and the names are a mix of young and old, hitters and pitchers, scout-adored and not. By its definition of “Good,” PECOTA tells us that a few of these prospects will become stars. Scouts have their eyes on a few, but PECOTA has its inclinations too—prospects it nearly pushes into “Very Good” territory without much scout support, for instance. Here, UPSIDE becomes a diamond-mining tool: Of these scout-neglected prospects, who have the best arguments for stardom based on their stats? This is perhaps the most interesting application of UPSIDE—to speculate about which of the relative no-names will eventually become big names.

But aside from analyzing PECOTA’s likes and dislikes, we’re also interested in comparing its rankings to qualitative ones, such as Jason Parks’ Top 101. This exercise can reveal what the model misses, which prospects may be underrated scouting-wise, and which both scouts and stat agree on. With two lists, let’s observe how they overlap:

  • 34 appear on both lists
  • 66 appear exclusively on PECOTA’s top 100
  • 66 appear exclusively on Parks’ top 101

Here we observe the nature of a purely stat-driven prospect ranking: It disagrees with a scout-based ranking two-thirds of the time. I appreciate this large figure—it shows how naïve a stat-driven list can be, given that scouts have access both to stats and to their own insight about players. It stresses that PECOTA thinks certain players aren’t getting enough credit, leading us to ask why. It also pushes us to consider how to improve PECOTA as a model.

We’ll examine the disagreements between PECOTA and BP’s Prospect Staff throughout the series, position by position and player by player.

The Hybrid Top 60
We can synthesize the Baseball Prospectus minds by combining both PECOTA’s and Jason Parks’ lists into one “BP” rank. Below, I’ve taken the geometric mean of the PECOTA Top 100 and Parks Top 101 ranking for each player. If the prospect didn’t make Parks’ 101, I assigned him a default Parks ranking of 150.

I also capped PECOTA rankings at 150, so anyone exceeding that number receives a PECOTA ranking of 150. This minimizes any outlying factors PECOTA couldn’t account for. For example, Lucas Giolito has a PECOTA ranking of 3,409 because of limited playing time; we’d rather not dock him for that. So for the purposes of the Hybrid Top 60, he sits in a 6,669-way tie as 150th on PECOTA’s rankings (that’s about how many players we ran PECOTAs for).

The formula in mathematical terms:


Rank

Name

Pos

Org

Age

PECOTA

JP101

1

Byron Buxton

CF

MIN

20

1

1

2

Oscar Taveras

CF

SLN

22

2

3

3

Carlos Correa

SS

HOU

19

3

5

4

Xander Bogaerts

SS

BOS

21

9

2

5

Javier Baez

SS

CHN

21

10

4

6

Kevin Gausman

RHP

BAL

23

5

10

7

Miguel Sano

3B

MIN

21

6

14

8

Addison Russell

SS

OAK

20

14

7

9

Gregory Polanco

CF

PIT

22

7

24

10

Jackie Bradley

CF

BOS

24

13

23

11

Tyler Glasnow

RHP

PIT

20

8

42

12

Joey Gallo

3B

TEX

20

4

95

13

George Springer

CF

HOU

24

21

20

14

Yordano Ventura

RHP

KCA

23

39

12

15

Marcus Stroman

RHP

TOR

23

20

27

16

Joc Pederson

CF

LAN

22

15

50

17

Francisco Lindor

SS

CLE

20

170

6

18

Noah Syndergaard

RHP

NYN

21

95

11

19

Taijuan Walker

RHP

SEA

21

150

8

20

Archie Bradley

RHP

ARI

21

415

9

21

Corey Seager

SS

LAN

20

35

44

22

Kevin Plawecki

C

NYN

23

11

--

23

Michael Roth

LHP

ANA

24

12

--

24

Lucas Giolito

RHP

WAS

19

3409

13

25

Josmil Pinto

C

MIN

25

36

56

26

Dylan Bundy

RHP

BAL

21

266

15

27

Jonathan Gray

RHP

COL

22

149

16

28

Bruce Rondon

RHP

DET

23

16

--

29

Kris Bryant

3B

CHN

22

816

17

30

Christian Vazquez

C

BOS

23

17

--

31

Austin Hedges

C

SDN

21

186

18

32

J.R. Murphy

C

NYA

23

18

--

33

Jameson Taillon

RHP

PIT

22

321

19

34

Max Stassi

C

HOU

23

19

--

35

Erik Johnson

RHP

CHA

24

43

67

36

Clint Frazier

CF

CLE

19

81

36

37

James Paxton

LHP

SEA

25

45

68

38

Pierce Johnson

RHP

CHN

23

34

91

39

Mark Appel

RHP

HOU

22

1918

21

40

Maikel Franco

3B

PHI

21

62

52

41

Oscar Hernandez

C

TBA

20

22

--

42

Robert Stephenson

RHP

CIN

21

464

22

43

Jonathan Singleton

1B

HOU

22

60

57

44

Stephen Pryor

RHP

SEA

24

23

--

45

Kyle Zimmer

RHP

KCA

22

104

34

46

Trevor Bauer

RHP

CLE

23

24

--

47

Nick Castellanos

LF

DET

22

98

37

48

Albert Almora

CF

CHN

20

2785

25

49

Danny Hultzen

LHP

SEA

24

25

--

50

Arodys Vizcaino

RHP

CHN

23

26

--

51

Eddie Butler

RHP

COL

23

716

26

52

Travis d'Arnaud

C

NYN

25

84

48

53

Brian Goodwin

CF

WAS

23

47

86

54

Domingo Santana

RF

HOU

21

27

--

55

Charlie Tilson

CF

SLN

21

28

--

56

Chris Owings

SS

ARI

22

298

28

57

Bubba Starling

CF

KCA

21

29

--

58

Adalberto Mondesi

SS

KCA

18

2236

29

59

Andrew Heaney

LHP

MIA

23

251

30

60

Alen Hanson

SS

PIT

21

30

--

While the inclusion of Parks’ grades balances this list into a respectable ranking, the influence of PECOTA is hardly lost. Note, for example, Mets’ catcher Kevin Plawecki, whom PECOTA quite likes; he retains the no. 11 ranking despite missing Parks’ top 101. Small-sample pitchers like Giolito and Mark Appel surface on this list too.

We’ll talk more about Plawecki when PECOTA takes on catching prospects next time.

Andrew Koo is an author of Baseball Prospectus. 
Click here to see Andrew's other articles. You can contact Andrew by clicking here

Related Content:  Prospects,  Minor Leagues,  PECOTA

35 comments have been left for this article. (Click to hide comments)

BP Comment Quick Links

jjf1041

How does Bubba Starling get ranked as 29th by Pecota? I used to be a true believer in him but no longer am. Does Pecota heavily weigh, or include at all, high school stats? Starling's performance in the minors has been unremarkable.

Apr 15, 2014 03:56 AM
rating: 3
 
yadenr

Yes, it seems that both he and Bauer have had pretty dismal performances so far but rank quite high on Upside...can you elaborate? Thanks, this was a good read.

Apr 15, 2014 08:43 AM
rating: 0
 
BP staff member Andrew Koo
BP staff

High school stats, no. Starling hasn't performed to our expectations of him, but he hasn't been awful. PECOTA's also giving him more credit for playing in a depressed run environment.

Apr 15, 2014 09:42 AM
 
jtwalsh

Thanks for resurrecting Pecota Takes on the Prospects. I always thought it was a fun alternative take on prospect evaluation. Taken for what it is, it is useful. The depth and quality of writing you have given to this subject is impressive. I guess Pecota is a sucker for catching prospects.

Apr 15, 2014 04:02 AM
rating: 9
 
BP staff member Andrew Koo
BP staff

Thanks--I hope that message does come across, that it's an alternative. By no means do I think PECOTA's prospect opinions supersede scout work, especially the great stuff Jason Parks does here.

Apr 15, 2014 09:46 AM
 
BP staff member Andrew Koo
BP staff

And by alternative, I mean complementary!

Apr 15, 2014 11:49 AM
 
mhmckay

It feels like there is a systematic bias in the PECOTA rankings against pitchers (12 of the top 13 are position prospects). Is that a function of TINSTAAPP or some other bias inherent in the system? Surprising to see the large gaps in the ratings even in pitchers in the high minors like Heaney or Taillon, let alone down to guys like Giolito ranked #3490 (!) by PECOTA.

Apr 15, 2014 04:10 AM
rating: 3
 
BP staff member Andrew Koo
BP staff

PECOTA will have some trouble with small-sample pitchers, and Giolito has less than 40 professional innings to his name. Which is why, for the purposes of the Hybrid Top 60, I capped his ranking at 150.

Apr 15, 2014 09:58 AM
 
alvinfan

Telvin Nash?

Man, that's the definition of one tool, right there. And he was injured the last two months of last season and is in EST right now.

Apr 15, 2014 05:07 AM
rating: 2
 
CRP13

One tool? C'mon, I've heard that he's a very nice guy.

May 01, 2014 09:27 AM
rating: 0
 
mshopoff

Is there an unintended bias towards catchers in UPSIDE? Perhaps not factoring that many comparables move out from the plate?

Apr 15, 2014 06:28 AM
rating: 0
 
gweedoh565

Andrew mentions this when discussing the bias towards SS and CF (2nd paragraph after the PECOTA Top 100 table). Certainly it's easy to assume that catchers, as part of the same side of the defensive spectrum, are treated the same way.

Apr 15, 2014 06:54 AM
rating: 1
 
nyyfaninlaaland

Interestingly Andrew points out that there are 11 catchers in Pecota's top 100, and 8 in Jason Parks. But only 2 appear in both.

These 2 methodologies have significant differences, and as Andrew commented early on, this is not intended as an alternative, or as a better tool, than a scouting approach.

Jason's evals may have a skew towards scouted tool based upside, while this is based on projections off park / league adjusted performance data.

As a Yanks fan found it interesting that the only prospect in Parks Top 101 was Sanchez - a catcher. And he's not here. Neither is Austin Hedges.

Apr 15, 2014 11:46 AM
rating: 3
 
doog7642

Thanks, Andrew and BP. This is fantastic, and I appreciate the various elements -- description of the stat and process, review of the old results, comparison with a scouting-based prospect list -- that you've woven together. Looking forward to the rest of the series, and perhaps eventually a further exploration of your line "It also pushes us to consider how to improve PECOTA as a model."

Apr 15, 2014 06:30 AM
rating: 3
 
BP staff member Andrew Koo
BP staff

Thanks! Rob McQuown deserves major credit for reviving UPSIDE. We're happy to bring it back at BP.

Apr 15, 2014 11:10 AM
 
fawcettb

There's something wrong with the way PECOTA prejudices catchers. And what gets Michael Roth such upside? Is PECOTA chuffed about players who have the same name as novelists?

Apr 15, 2014 06:38 AM
rating: 0
 
BP staff member Andrew Koo
BP staff

There's a slight favoritism on catchers, but not a huge one (Jason Parks has 8 in his top 101, PECOTA has 11, albeit ranked higher). It's something to explore in next week's piece.

As for Roth, 45 pro innings isn't the greatest sample to work from. Roth is also unusual in that 20 of those innings are in the majors, where he had decent ratios. Probably higher than he should be, but we won't hard-code PECOTA for such unusual cases.

Apr 15, 2014 10:38 AM
 
polishwonder

Can you do a similar table of the players that BA rated highly and were not included on Pecota's list in 2006 & 2007. It would be interesting to see if there were comparable Warp totals on those players.

Apr 15, 2014 08:17 AM
rating: 1
 
BP staff member Andrew Koo
BP staff

Yep! So in 2006, Nate Silver named 10 BA players that PECOTA weren't as high on:

Name BA Rank (PECOTA Rank) 7-Yr MLB time WARP
Chad Billingsley 7 (79) 2006-12 12.3
Ian Stewart 16 (72) 2007-13 4.6
Andy LaRoche 19 (54) 2007-13 1.1
Nick Markakis 21 (Unranked) 2006-12 15.6
Jon Lester 22 (Unranked) 2006-12 16.4
Carlos Gonzalez 32 (99) 2008-present 18.3+
Scott Olsen 34 (69) 2006-10 2.1
Jonathan Papelbon 37 (Unranked) 2006-12 13.9
Homer Bailey 38 (Unranked) 2007-13 8.2
Anibal Sanchez 40 (Unranked) 2006-12 8.5

They ended up totaling 101 WARP, compared to Nate's 80.

In 2007, he highlighted BA/Goldstein's picks of Bailey, Justin Upton, Tulo, Carlos Gonzalez, and Adam Miller--pretty solid group sans Miller.

Apr 15, 2014 13:46 PM
 
BirdlandPGH

PECOTA on prospects is exactly why I started subscribing to Baseball Prospectus. It is the most valuable and unique feature BP has to offer. Thank you for resurrecting it! I hope this is relaunched next year two months sooner so that we can use this information in our fantasy drafts.

Apr 15, 2014 09:02 AM
rating: 6
 
varmintito

Wow, PECOTA really hates Archie Bradley. Hope the scouting take is the accurate one, since I have him stashed in my roto league.

Apr 15, 2014 09:09 AM
rating: -2
 
ravenight

Really excited about this series. One question about the calculation of UPSIDE - you say it's "above-average" WARP. Above-average relative to what?

Correct me if I'm wrong, but the calculation seems to go like this:
- Find the 20 most-comparable seasons (which means the players who, at that point in their career, had had a career most similar to the one being considered).
- For Buxton, this would be Trout 2012, FMart 2009, Daniel Fields 2011, JUp 08, Heyward '10, Cutch '07, Angel Morales '10, Allen Hanson '13, Domingo Santana '13, Jaff Decker '10, Yelly '12, Luigi Rodriquez '13, Myers '11, Gose '11, Eddie Rosario '12, Billy Butler '06, Tabata '09, Snider '08, Nimmo '13, Taveras '12
- Starting with those seasons, get the actual or projected performance for each player in their best 5 years prior to age 28 or the 5 years following the comp if they were at least 24. It figures some average to compare those WARP values to, and sums the above-average ones.
- So that produces 20 5-year sums of WARP. For each, we double it (presumably to scale it to a similar level as the previous non-negative WARP version?) and multiply by similarity, then we add them all together and divide by the sum of all 20 similarities
- So now we have a number. What does this mean? For Buxton, the number is 219.7 which is way more than for anyone else. Yet his long-term PECOTA forecast (which is also supposed to be a weighted mean) has his best 5 years prior to age 28 as 4.5, 4.0, 4.8, 5.1, and 4.7 WARP, respectively. That totals to 23.1, so a) why is his UPSIDE not in the neighborhood of 20 x 23.1 = 462, and b) why would UPSIDE be more reliable than his PEAK5 WARP?

Apr 15, 2014 12:34 PM
rating: 0
 
ravenight

Thinking about this a little bit more, here's a guess:

Let's take a player like Bubba Starling, whose top 5 comparables are Brett Jackson, Daniel Fields, Julio Morban, Austin Jackson, and Michael Saunders.

Their PEAK5 WARPs are: -4*, -0.8, -6.4, 13.2, 6.1

The average is 1.62. The sum of the above-average ones, times 2, is 38.6, which is meant to represent an average PEAK5 of just-under 10, so I can't just divide by 5 to get the average it corresponds to, because it depends on how many players ended up counting as above-average.

*This one is approximate, since I didn't want to try to translate his minor league stats from last year into major-league WARP

Apr 15, 2014 12:55 PM
rating: 0
 
ravenight

To continue talking to myself here what happens with this example:

Guy A has 19 comps with PEAK5 of 0, and 1 with PEAK5 of 25, so a 95% chance of being replacement-level, and a 5% chance of being a 5 WARP/year player. UPSIDE = 50.

Guy B has 15 comps with PEAK5 of -5, 4 comps with -2, and one with 25. So the average is -2.9, meaning that the -2 guys count as above average? So this guy has upside of only 34.

Maybe that's alright though - if your floor is basically replacement level but you have a chance at being an MVP, maybe you are better than a prospect who will either flame out or become an MVP.

Apr 15, 2014 13:18 PM
rating: 0
 
BP staff member Andrew Koo
BP staff

Yep, these are the main steps of the process. In regards to Buxton, UPSIDE is the composite of above-average WARP values, so subtract a little over 10 WARP (5 x 2) to sum the "Wins Above Average," assuming an average player produces ~2 WARP.

The long-term PECOTA forecast for Buxton has him playing full seasons (600+ PA) while UPSIDE's comparables does not necessarily assume so.

For any player, they'll inevitably have comparables with below-average performance, which will lower their UPSIDE.

Apr 15, 2014 13:16 PM
 
ravenight

Oh, so average really is league-average, then, not average of the comps?

Apr 15, 2014 13:21 PM
rating: 0
 
BP staff member Andrew Koo
BP staff

Yes. Comparables that produce below league average are zeroed out.

Apr 15, 2014 13:24 PM
 
ravenight

Interesting. And does it use projections for the comps, or only players who had actual production that could be compared?

Assuming it uses projections (given the comparables list on the PECOTA cards), I wonder how it would change if only completed seasons were used (so therefore for prospects all the comps have to be from 6-10 years ago or more)

Apr 15, 2014 15:03 PM
rating: 0
 
dREaDS Fan

How come no sidebar authored by Prof Parks slagging off the PECOTA prospect approach?

Kidding.

Very much looking forward to this series ... with eyes wide open as to the limitations of a numbers-only approach.

Apr 15, 2014 12:48 PM
rating: 3
 
Plucky

I'm an Astros homer and I don't even know who Jason Martin or Kyle Smith are.

I'm happy to see that PECOTA believes in Domingo Santana's numbers, but that is of course exactly what PECOTA does by construction

Apr 15, 2014 13:12 PM
rating: 0
 
CRP13

You should. Great prospects. Martin = highly-touted HS CF that was drafted in 2013, and Smith is a #1-#2 ceiling SP that was traded from KC last year for Justin Maxwell, I believe.

May 01, 2014 09:24 AM
rating: 0
 
Matthew W

80 WARP is a lot of value for players that could have been acquired on the cheap. I miss Nate

Apr 16, 2014 05:13 AM
rating: 2
 
Nathan Aderhold

This was fun! Thanks, Andrew.

I'm intrigued about Michael Roth's high placement on the list. Given that his numbers across the board have been unremarkable thus far, it makes me wonder what kind of weight PECOTA puts on a player's trajectory in the minors.

Roth, for instance, jumped from Rookie Ball to Double-A between '12 and '13, then hopped directly into the Angels bullpen after just a week in the Texas League.

Apr 17, 2014 19:00 PM
rating: 0
 
Nathan Aderhold

Whoops, never mind. Remind me to refresh the page before commenting.

Apr 17, 2014 19:30 PM
rating: 0
 
CRP13

Telvin Nash, #100. Sure, he's probably got 40+ HR power. But that 40% strikeout rate below AA...yikes.

I love this list because it's so different.

May 01, 2014 09:25 AM
rating: 0
 
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