2013 Fantasy BaseballBrett TalleyFantasy BaseballFront Office

2013 Fantasy Baseball: 1B Projections and Roto Ratings

Source: Mitchell Layton/Getty Images North America
Source: Mitchell Layton/Getty Images North America

This is the eighth installment of our projection series. We are posting a series of articles in which we project the roto stats for all hitters who could be useful in mixed leagues. The projections and “Roto Ratings” for each player are available to those who subscribe to our premium content via our “Front Office” package. Today we have first basemen. We will have complete list of all hitters on Friday.

Big thanks to my buddy Brian Sager (@TheRealSAG) for helping me develop this idea and for talking through the whole thought process with me.

When analyzing a player’s Fangraphs page, you sort of automatically project the stats that you think the player will have in the upcoming season. But because you can’t memorize loose projections for 300+ players, you have to repeatedly go back to a player’s page and go through the mental process of projecting them again. But as a service to our premium content subscribers, I have decided to do the projections myself and make them available on the site.

The first step in the process is simply to project a range of possible outcomes for each player while assuming he plays a full season. To project those possible outcomes I use a variety of stats. To project batting average I factor in plate discipline skills (K%, BB%, Contact%, Swing%, Z-swing%, O-Swing%) and batted ball profiles (LD%, GB%, FB%).  To predict home runs I again use the batted ball profiles as well as HR/FB rate from past years. To predict runs, RBI and steals I consider past performance in those categories, stolen base success rate, and where a player will be hitting in the lineup.

Every player can’t play every day, so you have to approximate how many games you think the player will miss and then fill in those games missed with the stats of the type of guy you might find on the waiver wire. To find that replacement level, I took the stats from the first basemen that were owned in less than 70% but more than 30% of ESPN leagues at the end of last year and averaged their stats. A replacement level guy at first base will give you the following stat line over the course of a season:

Category AVG HR SB R RBI
Stats .241 21 1 57 60

 

The next step is to take the stats you think you’ll get from a player for the amount of games you project him to play once you factor in injury risk and playing time concerns. For example, I projected Allen Craig for 135 games, so I multiplied all my projections for him by 0.87 (135 games is 87% of 155 games). Then I took my replacement level stat line and multiplied all those numbers by the remaining 0.13. Then you add those two numbers together to get the final stat line you’d expect to get from 135 games from Craig and 20 games from a replacement level player. Craig’s projection after accounting for playing time and adding in a replacement player for his games missed looks like this:

Name

G

PA

AVG

HR

SB

R

RBI

Allen Craig

155

673

.302-.308

28-31

3.0-4

100-106

82-86

135

586

0.297

28

3

97

81

 

After I got my final stat line, I decided to come up with a formula to use the projections to do rankings. This system I came up with is admittedly crude, but I think it does a pretty decent job of ranking the players.

I plan on ranking about 200 hitters, so I took the 200 hitters with the most plate appearances last season and created tiers for each roto category. For example, 20 guys hit above .307 last year. The next 20 guys hit between .293 and .306. So if I projected a guy to hit .308, I assigned him 10 points for average. If I projected him to hit between .293 and .306, I assigned him nine points, etc, etc. Because I projected ranges, I used the midpoint to see which tier someone fit into. I projected Albert Pulos to hit between .292 and .296. The midpoint there was .294. That fell within the second tier so I assigned Pujols nine points for average. Below are the tiers I used:

AVG HR SB R RBI
10 >.307 >31 >29 >93 >97
9 .293-.306 25-30 20-28 86-92 86-96
8 .286-.292 23-24 14-19 81-85 78-85
7 .275-.285 19-22 11.0-13.0 74-80 72-77
6 .270-.274 16-18 7.0-10.0 69-73 65-71
5 .260-.269 14-15 5.0-6.0 65-68 59-64
4 .250-.259 12.0-13.0 3.0-4.0 59-64 55-58
3 .241-.249 9.0-11.0 2 54-58 49-54
2 .229-.240 6.0-8.0 1 47-53 40-48
1 <.229 <6 0 <46 >39

 

 

 

 

 

 

After I assigned a player a point total for each individual category I added them all up and gave each player a score which I am calling their “Roto Rating.” I also gave a few bonus points for those players that I projected to produce truly elite numbers in a given category. Below are the projections and Roto Ratings for my top 30 first basemen. Enjoy!

[am4show have=’p4;p7;p3;’ guest_error=’Front Office’ user_error=’Front Office’ ]

Name

G

PA

AVG

HR

SB

R

RBI

Bonus

Total

Albert Pujols

155

676

.292-.296

33-36

5.0-7

94-99

109-113

9

10

5

10

10

1

45

Joey Votto

155

692

.313-.319

24-27

7.0-9

93-98

92-98

10

9

6

10

9

1

45

Edwin Encarnacion

155

652

.275-.281

32-36

8.0-12

88-92

99-105

148

622

0.276

33

10

88

100

7

10

6

9

10

42

Prince Fielder

155

661

.296-.302

30-33

1

86-92

106-114

9

10

2

9

10

1

41

Paul Goldschmidt

155

627

.279-.285

23-27

11.0-14

82-86

88-94

7

9

7

8

9

40

Freddie Freeman

155

653

.281-.287

24-27

2.0-4

93-97

96-102

7

9

4

10

10

40

Allen Craig

155

673

.302-.308

28-31

3.0-4

100-106

82-86

135

586

0.297

28

3

97

81

9

9

4

10

8

40

Adrian Gonzalez

155

668

.292-.298

26-29

1

89-93

104-108

9

9

2

9

10

39

Eric Hosmer

155

648

.282-.288

18-21

14-17

81-85

82-88

7

7

8

8

8

38

Anthony Rizzo

155

656

.278-.284

25-29

8.0-10

76-81

83-88

7

9

6

7

9

38

Billy Butler

155

663

.298-.304

19-23

1.0-2

74-80

94-100

9

7

2

7

10

35

Corey Hart

155

647

.266-.272

27-31

5.0-8

90-94

80-84

120

501

0.263

27

6

84

77

5

9

5

8

7

34

Paul Konerko

155

644

.290-.294

26-30

0

72-76

86-92

142

590

0.288

27

0

73

87

8

9

1

6

9

33

Garrett Jones

155

625

.260-.266

27-30

3.0-4

72-76

90-94

135

544

0.26

28

3

72

88

5

9

4

6

9

33

Lance Berkman

155

651

.270-.276

18-21

2.0-3

88-92

93-97

128

538

0.268

20

2

84

89

5

7

3

8

9

32

Adam LaRoche

155

650

.270-.276

26-29

1

69-75

90-96

142

595

0.27

27

1

71

90

6

9

2

6

9

32

Ike Davis

155

629

.256-.264

30-33

0

68-73

94-99

5

10

1

6

9

31

Mark Teixeira

155

660

.247-.253

28-32

2

84-88

96-102

112

477

0.248

27

2

78

88

3

9

3

7

9

31

Chris Davis

155

627

.264-.270

26-29

1.0-2

69-73

78-82

142

574

0.265

27

1

70

78

5

9

2

6

8

30

Brandon Moss

155

643

.247-.253

23-26

3.0-4

77-83

85-89

120

498

0.248

24

3

75

81

3

8

4

7

8

30

Ryan Howard

155

637

.244-.252

28-32

0

81-85

92-98

135

555

0.247

29

0

80

90

3

9

1

7

9

29

Mitch Moreland

155

592

.264-.270

23-26

2.0-3

66-70

81-85

120

486

0.261

24

2

65

78

5

8

3

5

8

29

Brandon Belt

155

608

.266-.274

13-17

14-17

59-63

70-76

148

581

0.267

15

15

61

72

5

5

8

4

7

29

Mark Reynolds

155

615

.220-.226

28-31

3.0-4

74-78

80-84

142

564

0.224

29

3

74

80

1

9

4

7

8

29

Chris Carter

155

602

.242-.248

26-29

3.0-4

63-67

70-74

3

9

4

5

7

28

Justin Morneau

155

634

.272-.280

23-26

0

68-72

83-87

128

524

0.27

24

0

68

81

6

8

1

5

8

28

Kendrys Morales

155

618

.272-.280

25-28

0

64-68

73-77

128

511

0.27

26

0

64

72

6

9

1

4

7

27

Adam Dunn

155

651

.206-.212

29-32

0

71-77

81-85

1

9

1

7

8

26

Carlos Pena

155

618

.212-.218

21-24

2.0-3

70-74

75-79

1

8

3

6

7

25

Justin Smoak

155

609

.234-.240

21-25

1

58-62

64-69

128

503

0.238

23

1

59

65

2

8

2

4

6

22

[/am4show]

Previous post

30 Prospects in 30 Days: Kolten Wong - 2B - St. Louis Cardinals

Next post

Keep it on the DL: Late Round Pitching Stashers for A Late Season Run

No Comment

Leave a reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.