Well I basically decided to do some work on this for my own interest, to find a fairly simple but effective way of calculating player values in different systems.

So I used the calculation I suggested above above, ie.;

value created in a stat = (score in stat – mean of that stat)/(standard deviation of stat)

Obviously you need to get a hold of mean and standard deviation values. A point on that, subtracting the mean is not strictly necessary, in doing so you get an indication of value created or lost in that stat over a replacement player, but when comparing two players the difference would cancel out. It basically gives a datum (zero-line) at average value, that theoretically could make it possible to compare apples and pears (or in our case hitters and pitchers).

I created my list of values of mean and standard deviation from this years stats, which I took from J35J / Jason’s excellence spreadsheet recently posted on this forum (http://www.fantasybaseballcafe.com/foru ... p?t=240400). It’s an excellent resource which I really appreciate if you see this Jason.

I limited the stats to standard 5x5 to get a baseline to see if the maths work out. I limited the field to all hitters with 450+ ab’s (300+ for catchers). Starters with 100 IP’s and all relief pitchers in the spreadsheet (as it was already limited to the only 60 commonly fantasy relevant pitchers)

Furthermore I haven’t treated each stat exactly the same.

For hitting I have simply used the formula above for Runs, Hr’s RBI’s and SB’s, however as AVG is not a cumulative stat I believe it should be treated slightly different. For instance, Cano and Jeter had AVG’s of .342 and .343 respectively, but as Jeter had 141 extra at bats, his contribution would have a greater impact, making him more valuable. Therefore for AVG I have used the above formula, but then adjusted it by multiplying by the ratio of (players at bats) / (mean at bats).

For pitching it can be seen that ERA and WHIP are both similar cases to AVG and have been treated as such (adjusted for Innings pitched), with the exception that the value has been reversed (ei. a decrease is better!). However as many leagues are limited innings, and a good manager would normally use the entire quota (or near too) I have also treated K’s SV’s and Win’s the same way. My explanation of why is as follows, a starting pitcher who gets 100k’s in 200 ip’s has lost you value, because he has limited your ability to succeed in strikeouts, whereas a reliever who gets 100k’s in 60ip has gained you value, therefore using just the cumulative number would not give a fair reflection of the value added or lost. To take this into account I have simply replaced the K SV and Win stats and replaced them with K/9 SV/9 and Win/9.

For clarity here is a full summary of the calculations used

Hitting:

Runs Value = (runs – mean)/ standard deviation

HR Value = (HR’s – mean)/ standard deviation

RBI Value = (RBI’s – mean)/ standard deviation

SB Value = (SB’s – mean)/ standard deviation

AVG Value = (AB’s / “AB mean”) * (AVG – mean)/ standard deviation

Pitching

ERA Value = (IP / “IP mean”) * (mean - ERA)/ standard deviation

WHIP Value = (IP / “IP mean”) * (mean - WHIP)/ standard deviation

K/9 Value = (IP / “IP mean”) * (K/9 – mean)/ standard deviation

Wins/9 Value = (IP / “IP mean”) * (Wins/9 – mean)/ standard deviation

SV/9 Value = (IP / “IP mean”) * (SV/9 – mean)/ standard deviation

Total Value = Sum of individual components for that player

And the various values used in this format:

Catergory = mean, standard deviation

Runs = 77.4, 21.9

HR’s = 18.4, 11.3

RBI’s = 75.0, 24.9

SB’s = 9.5, 12.6

AVG = .2829, .0247

AB’s = 516.7

ERA = 4.003, 1.104

WHIP = 1.317, 0.188

K/9 = 7.266, 2.105

SV/9 = 0.778, 1.633

Wins/9 = 0.541, 0.189

IP = 140.3

Now for the interesting part, verification, I now used these formulas on this years stats to see how it would rank the players, here’s the top 101:

Rank Value Position Player

1 8.92 1B Albert Pujols

2 8.31 1B Ryan Howard

3 7.51 SS Jose Reyes

4 7.35 2B Alfonso Soriano

5 7.28 SP Johan Santana

6 7.22 SS Derek Jeter

7 6.92 OF Matt Holliday

8 6.87 1B David Ortiz

9 6.52 2B Chase Utley

10 6.44 OF Lance Berkman

11 6.40 OF Jermaine Dye

12 6.31 OF Miguel Cabrera

13 6.29 3B Garrett Atkins

14 6.27 OF Carlos Beltran

15 6.23 OF Vladimir Guerrero

16 6.01 OF Carlos Lee

17 5.81 RP Joe Nathan

18 5.74 1B Justin Morneau

19 5.70 3B Alex Rodriguez

20 5.50 SP Francisco Liriano

21 5.45 OF Carl Crawford

22 5.28 3B David Wright

23 4.95 SS Jimmy Rollins

24 4.95 DH Travis Hafner

25 4.87 SS Hanley Ramirez

26 4.83 OF Grady Sizemore

27 4.64 RP Takashi Saito

28 4.63 OF Vernon Wells

29 4.60 SS Miguel Tejada

30 4.55 1B Paul Konerko

31 4.55 OF Ichiro Suzuki

32 4.47 RP Jonathan Papelbon

33 4.30 1B Jim Thome

34 4.19 RP J.J. Putz

35 4.17 OF Jason Bay

36 4.16 OF Andruw Jones

37 4.15 OF Bobby Abreu

38 4.09 OF Raul Ibanez

39 4.00 3B Aramis Ramirez

40 3.90 SS Rafael Furcal

41 3.90 SS Carlos Guillen

42 3.78 RP B.J. Ryan

43 3.74 OF Johnny Damon

44 3.66 RP Francisco Rodriguez

45 3.45 SP Jered Weaver

46 3.35 RP Billy Wagner

47 3.34 SP Chris Carpenter

48 3.25 RP Francisco Cordero

49 3.22 OF Manny Ramirez

50 3.16 RP Mariano Rivera

51 3.05 1B Mark Teixeira

52 3.04 RP Chad Cordero

53 2.95 SP Mike Mussina

54 2.93 RP Michael Young

55 2.84 OF Gary Matthews Jr.

56 2.77 CA Joe Mauer

57 2.75 2B Michael Cuddyer

58 2.60 OF Chipper Jones

59 2.55 RP Joel Zumaya

60 2.52 SP John Smoltz

61 2.50 SP Brandon Webb

62 2.49 RP Cla Meredith

63 2.47 SP Carlos Zambrano

64 2.42 SP Roger Clemens

65 2.42 OF Torii Hunter

66 2.39 RP Dennys Reyes

67 2.36 RP Huston Street

68 2.34 1B Carlos Delgado

69 2.34 SS Troy Glaus

70 2.30 2B Dan Uggla

71 2.30 SP Scott Kazmir

72 2.29 SS Bill Hall

73 2.22 3B Scott Rolen

74 2.22 RP Scot Shields

75 2.20 1B Jason Giambi

76 2.18 1B Lyle Overbay

77 2.16 3B Ryan Zimmerman

78 2.15 DH Frank Thomas

79 2.14 SP Roy Oswalt

80 2.12 RP Chris Ray

81 2.01 OF Juan Pierre

82 1.99 SP C.C. Sabathia

83 1.97 2B Chone Figgins

84 1.93 RP Tom Gordon

85 1.93 SP Chris Young

86 1.92 2B Freddy Sanchez

87 1.90 OF Magglio Ordonez

88 1.88 RP Brian Fuentes

89 1.87 RP Trevor Hoffman

90 1.87 RP Mike Gonzalez

91 1.84 1B Nick Johnson

92 1.77 SP Roy Halladay

93 1.76 RP Akinori Otsuka

94 1.74 RP Fernando Rodney

95 1.71 OF Mike Cameron

96 1.67 1B Adam LaRoche

97 1.66 2B Ray Durham

98 1.66 2B Felipe Lopez

99 1.65 OF Nick Swisher

100 1.62 SP Curt Schilling

101 1.61 CA Brian McCann

Not perfect. I notice a potential bias towards closers, and a definite one against starting pitching, but at least within a single position, saying hitting or starting pitching I think it makes a fair comparison of this seasons performance.

Obviously it also doesn’t take into any account positional scarcity either.

For all my complication through over explanation it is actually a quick and simple thing to do. It should be easy to apply to other non-standard stats, and gives a fair weighting.

I mainly did this for my own interest, but if there are any comments or things people notice, suggestions even, I’d be pleased to hear them.

Also I have given a little consideration to positional scarcity for hitting, and roster spot premium for pitching (i.e. 17 relivers each giving 70 innings would give you your 1250 high quality innings. it is the lack of roster spots that decreases their value and increases a starters value).

Any ideas on how to deal with these factors would be very interesting.

Iain (UIS)

p.s. (yes i know i am hopelessly geeky - and sorry if this recovers previous topics, i'm new, i did it mostly for my own interest, and if it bores you, you can skip it)