2007 play logs from FanGraphs shows that Willy Taveras was a very poor base stealer for the Rockies last year.  While his raw steal total was high, his percentage was very poor in high leverage situations.  The average Leverage Index on a Taveras stolen base attempt last year was 1.28 (1.0 is average leverage index).  The leverage index on a successful attempt was 1.14 and the average leverage index on an unsuccessful attempt was a whopping 1.834.  This means that last year Taveras was good at stealing lesser important bases, but quite poor at stealing bases of importance.  So much so that he actually hurt the Rockies last year stealing bases.  His total WPA (Win Probability Added) was -0.186.  His linear weights wins added was .366, but linear weights does not take game context into consideration like WPA does.  Of the 10 top base-stealers from the NL West in 2007 that I looked at, Taveras had the worst WPA.  The best was Juan Pierre with a 0.648 WPA, followed by Eric Byrnes with a 0.419 WPA.

vr, Xeifrank

I ran similarity scores for every NL West pitcher using 2008 ZIPS Projections adjusted for park.  The three stats I looked at were HR/9, K/9 and BB/9.  Those are the only three factors this study looked at.  It was meant to compare how similar or different each NL West pitcher was to each other for the 2008 season only.  Here are the Rockie starting pitchers three most similar NL West pitchers and three least similar NL West pitchers.

Pitcher: Cook
Most: 1. Maddux, 2. Lowe, 3. Kuroda
Least: 1. Prior, 2. Johnson, 3. Jimenez

Pitcher: Francis
Most: 1. Owings, 2. Lowe, 3. Penny
Least: 1. Webb, 2. Maddux, 3. Jimenez

Pitcher: Morales
Most: 1. Zito, 2. Lowry, 3. Hensley
Least: 1. Maddux, 2. Webb, 3. Germano

Pitcher: Hirsh
Most: 1. Hensley, 2. Lowry, 3. Owings
Least: 1. Webb, 2. Maddux, 3. Cook

Pitcher: Jimenez
Most: 1. Morales, 2. K.Wells, 3. Zito
Least: 1. Maddux, 2. Kuroda, 3. Haren

Pitcher: K.Wells
Most: 1. Lowry, 2. Wolf, 3. Zito
Least: 1. Webb, 2. Maddux, 3. Kuroda

Pitcher: Redman
Most: 1. Hensley, 2. Lowry, 3. Hirsh
Least: 1. Webb, 2. Johnson, 3. Maddux

Two most similar Rockie pitchers
Jimenez/Morales

Two least similar Rockie pitchers
Jimenez/Cook

Which pitcher do you think has the most/least favorable comparisons?

vr, Xeifrank

Well, pretty soon they will.  I've taken the steps of calculating the WAR (Wins Above Replacement) of each NL West roster.  To do this I am using 2008 ZIPS Projections (then adjusting for park) and making some modifications for projected playing time.  With the Diamondbacks this isn't too big of a deal, but with the outfield and 3B mess in LA it is.  Generally, I am giving starters a playing time coefficient of 0.85 and bench players 0.25 and where position battles are unsettled I've split the difference to some degree.  I've also done this so I can compare the team WAR totals to what I got in my simulator when playing each team through their 2008 schedule 25 times.  Here are the results below.  Keep in mind that this is just my work, and do not claim to be related to Bill James, and I must give credit to Tango Tiger and the USSM Blog for their tutorials on how to calculate WAR.

Notes: Units are in Wins.
Hitting:
LAD: 19.46
ARI: 18.72
COL: 18.67
SD: 18.67
SF: 11.35

Starting Rotations:
LAD: 7.07
ARI: 5.86
COL: 4.46
SF: 3.82
SD: 3.76

Bullpens
ARI: 13.72
LAD: 10.96
SF: 9.41
SD: 8.06
COL: 6.81

Team Totals: (WAR / Simulator)
ARI: 88.30 / 82.36
LAD: 87.50 / 85.88
SD: 80.48 / 82.76
COL: 79.95 / 81.68
SF: 74.57 / 75.16

Diamondbacks breakdown:
C-C.Snyder: 1.49
C-M.Montero: 1.20
1B-C.Jackson: 2.05
2B-O.Hudson: 2.84
3B-M.Reynods: 2.39
3B-C.Tracy: 0.62
SS-S.Drew: 1.33
SS-A.Ojeda: 0.55
LF-E.Byrnes: 2.60
CF-C.Young: 2.24
RF-J.Upton: 0.42
CF-C.Burke: 0.46
LF-J.Salazar: 0.52

P-B.Webb: 5.41
P-D.Haren: 3.33
P-R.Johnson: 1.91
P-D.Davis: 1.75
P-M.Owings: 1.48
P-B.Lyon: 0.99
P-T.Pena: 1.15
P-C.Qualls: 1.07
P-D.Slaten: 0.95
P-Y-Petit: -0.22
P-J.Cruz: 1.48
P-B.Medders: 0.30

I am using my baseball simulator program to rank the teams in each of the six divisions.  I have just completed running sims on the AL West (now that the Bedard trade is final).  I play 2500 games pitting each team against each of the other three teams in the division.  In each matchup 2500 games are played with the #1 pitcher going up against the other teams #1 pitcher, so on for all five starters.  This is not a perfect study as there is no consideration to injuries or players more likely to lose playing time due to injuries than others.  Nonetheless, the paprameters are equal for all teams.  Surprisingly, the Rangers finished in 2nd place in the AL West, behind the Angels.  ZIPS dislikes the Mariners offense and they finished last, even with Bedard on the team.  I am also running seasonal simulations, playing through the 2008 schedule for each team to get an average win total for each team (that will come later).

Link to study

Results:

1. Angels
   
2. Rangers
   
3. A's
   
4. Mariners

I am using my baseball simulator that I wrote last year to rank all 6 baseball divisions based on 2008 ZIPS Projections.  The simulator uses advanced sabermetric algorithms to pit two teams against each other taking into account nearly every facet of a baseball game.  It is still light on modelling defense, as there doesn't seem to be any one defensive metric that the great minds can agree to.  In this study I took roster depth charts from both Rototimes and Yahoo and played each team against each of the other divisional teams, with #1 pitchers going up against #1 pitchers and #2 pitchers going up against #2 pitchers etc..., each game was simulated 2000 times, played at both home and away (park factors involved).  All the games are summed up and an average winning percentage is calculated.  Below are the AL Central Results.  The White Sox, obviously did not fair too well in this study.  ZIPS is not particularly kind to the ChiSox.  ZIPS creator Dan Szymboski made this comment, "they're no longer even a heavy favorite to beat out the Royals for 4th place in the division".  I am waiting for the Bedard trade to be official before posting the AL West/East rankings.

1. Detroit .5459
   
2. Cleveland .5230
   
3. Minnesota .5112
   
4. Kansas City .4639
   
5. Chicago .4586

vr, Xeifrank

I am using my baseball simulator that I wrote last year to rank all 6 baseball divisions based on 2008 ZIPS Projections.  The simulator uses advanced sabermetric algorithms to pit two teams against each other taking into account nearly every facet of a baseball game.  It is still light on modelling defense, as there doesn't seem to be any one defensive metric that the great minds can agree to.  In this study I took roster depth charts from both Rototimes and Yahoo and played each team against each of the other divisional teams, with #1 pitchers going up against #1 pitchers and #2 pitchers going up against #2 pitchers etc..., each game was simulated 2000 times, played at both home and away (park factors involved).  All the games are summed up and an average winning percentage is calculated.  Below are the AL Central Results.  I am waiting for the Bedard trade to be official before posting the AL West/East rankings.

1. Detroit .5459
   
2. Cleveland .5230
   
3. Minnesota .5112
   
4. Kansas City .4639
   
5. Chicago .4586

vr, Xeifrank

NL East - Winter Rankings



Rankings were created by plugging 2008 ZIPS Projections into the baseball game simulator that I wrote.  The simulator uses advanced sabermetrical algorithms to pit two teams against each other.  Each NL East team faced off against each of the other NL East teams in a round robin format.  A format in which each teams #1 starter played 1000 home and away games against the other teams #1 starter, the same thing for the #2 vs #2 and so on.  All wins were added up and averaged.  All stats/projections were adjusted to the park they were played in (3 year park adjusted averages).



Results

1. NY Mets .5424
   
2. ATL Braves .530
   
3. PHI Phillies .508
   
4. WAS Nationals .471
   
5. FLA Marlins .449
   

vr, Xei

NL East - Winter Rankings



Rankings were created by plugging 2008 ZIPS Projections into the baseball game simulator that I wrote.  The simulator uses advanced sabermetrical algorithms to pit two teams against each other.  Each NL East team faced off against each of the other NL East teams in a round robin format.  A format in which each teams #1 starter played 1000 home and away games against the other teams #1 starter, the same thing for the #2 vs #2 and so on.  All wins were added up and averaged.  All stats/projections were adjusted to the park they were played in (3 year park adjusted averages).



Results

1. NY Mets .5424
   
2. ATL Braves .530
   
3. PHI Phillies .508
   
4. WAS Nationals .471
   
5. FLA Marlins .449
   

vr, Xei

The series moves back to Cleveland 1-1 and fans of both sides have probably caught up on their sleep after an exciting Game #2 thriller.  In that Game #2, my simulator gave the Indians a 51.16% win probability while Vegas only gave them a 43.48% win probability.  What does the simulator and Vegas say about the Game #3 matchup between Dice-K and Westbrook?

Game #3 Win Probabilities:

LV Hilton Sports Book: Red Sox 53.49%
Xeifrank's Simulator:  Red Sox 50.76%

Both sides predict a very even game.  The simulator gives a slight nod to the BoSox even though the results are within the margin of error, making this game pretty much a tossup for the simulator.

Best of luck.

vr, Xeifrank

Well, here you are, one game away from a trip to the World Series.  There's still some business to take care of first, a 4th victory over the Diamondbacks.

The simulator was giving more love to the Rockies in the first two games, especially in Game #2 when the simulator gave the Rockies a 57.5% chance of winning and Vegas a 48.78%.  In Game #3, we finally saw Vegas and the betting public come to their senses and now in Game #4 they seem to be overdosing on the Rockie kool-aid a bit.  In Game #4 the following win probabilities have been posted.

LV Hilton Sports Book: Rockies 62.69%
Xeifrank's Simulator:  Rockies 52.60%

Vegas is expecting a blow-out, perhaps they are expecting the DBacks to rollover and play dead, down 3 games to nil.  Or perhaps Vegas is just expecting a flood of money to come in on the Rockies and are moving the spread way up to even out the bets??  The simulator is still expecting a close game, probably within a run or two given the 52.6% win probability.

vr, Xei