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)