AL over and under-performing teams

Posted: March 8, 2014 in Managers, Projections

If anyone is out there (hello? helloooo?), as promised, here are the AL team expected winning percentages and their actual winning percentages, conglomerated over the last 5 years. In case you were waiting with bated breath, as I have been.

Combined results for all five years (AL 2009-2013), in order of the “best” teams to the “worst:”

Team

My WP

Vegas WP

Actual WP

Diff

My Starters

Actual Starters

My Batting

Actual Batting

NYA

.546

.566

.585

.039

98

99

.30

.45

TEX

.538

.546

.558

.020

102

95

.14

.24

OAK

.498

.490

.517

.019

104

101

-.08

.07

LAA

.508

.526

.522

.014

103

106

.07

.17

TBA

.556

.544

.562

.006

100

102

.24

.17

BAL

.460

.452

.463

.003

110

115

-.03

-.27

DET

.548

.547

.550

.002

97

91

.21

.31

BOS

.546

.596

.546

.000

99

98

.26

.36

CHW

.489

.450

.488

-.001

99

97

-.16

-.29

TOR

.479

.482

.478

-.001

106

107

-.05

.12

MIN

.468

.469

.464

-.004

108

109

-.07

-.07

SEA

.462

.464

.446

-.016

106

106

-.26

-.36

KCR

.474

.460

.444

-.030

108

106

-.22

-.28

CLE

.492

.469

.462

-.030

108

109

.13

.01

HOU

.420

.420

.386

-.034

106

109

-.46

-.61

I find this chart quite interesting. As with the NL, it looks to me like the top over-performing teams are managed by stable high-profile, peer and player respected guys – Torre, Washington, Maddon, Scioscia, Leyland, Showalter.

Also, as with the NL teams, much of the differences between my model and the actual results are due to over-regression on my part, especially on offense. Keep in mind that I do include defense and base running in my model, so there may be some similar biases there.

Even after accounting for too much regression, some of the teams completely surprised me with respect to my model. Look at Oakland’s batting. I had them projected as a minus -.08 run per game team and somehow they managed to produce .07 rpg. That’s a huge miss over many players and many years. There has to be something going on there. Perhaps they know a lot more about their young hitters than we (I) do. That extra offense alone accounts for 16 points in WP, almost all of their 19 point over-performance. Even the A’s pitching outdid my projections.

Say what you will about the Yankees, but even though my undershooting their offense cost my model 16 points in WP, they still over-performed by a whopping 39 points, or 6.3 wins per season! I’m sure Rivera had a little to do with that even though my model includes him as closer. Then there’s the Yankee Mystique!

Again, even accounting for my too-aggressive regression, I completely missed the mark with the TOR, CLE, and BAL offense. Amazingly, while the Orioles pitched 5 points in FIP- worse than I projected and .24 runs per game worse on offense, they somehow managed to equal my projection.

Other notable anomalies are the Rangers’ and Tigers’ pitching. Those two starting staffs outdid me by seven and six points in FIP-, respectively, which is around 1/4 run in ERA – 18 points in WP. Texas did indeed win games at a 20 point clip better than I expected, but the Tigers, despite out-pitching my projections by 18 points in WP, AND outhitting me by another 11 points in WP, somehow managed to only win .3 games per season more than I expected. Must be that Leyland (anti-) magic!

About these ads
Comments
  1. alex says:

    Hi.
    Just to let you know there are some of us out here. I never comment but I always read yours and Tango’s blog.

    Good luck and keep it coming from a dominican who loves baseball living in Ireland.

    • MGL says:

      Thanks! Two great places – Dominican Republic and Ireland! I’ve been to the former but never to the latter. As an avid golfer, I will definitely make it out to golf’s birthplace (more or less) one of these days!

  2. Tim says:

    Awesome stuff! Just for fun this time, knowing this was coming out, I wrote down my uneducated guesses of how this would come out. My guesses were solely based on my perception of how these teams performed over/under as to what I vaguely remembered the vegas win totals to be. (I know, really scientific, right?):

    Oak, Texas, Rays, Red Sox, Yankees, Detroit, CWS, Sea, Bal, Angles, Tor, Cle, KC, Twins, Astros

    I nailed the Astros in last (a gimmie) I had Cleveland and KC, and within a couple of slots, and I had Tex and Oak in the top three. I only missed badly on the Yankees and LAA probably due to personal bias, perception and faulty heuristics. Also some recency bias for sure.

    Again, really, really great work and very interesting stuff. The underestimation of Oakland is fascinating. As a fan of the Rangers and watching lots of AL west games, I constantly am asking myself how Oakland ever scores, but they sure do.

    A couple of questions:

    You mentioned the managers, do you think this table is indicative of a manager’s value?

    Also, just curious, how long did it take you to put this together?

    • MGL says:

      Thanks. Yeah, I wasn’t surprised that the Yankees over-performed my model, but I was a little surprised that they over-performed Vegas by so much (19 points in WP). Vegas, as you know, typically loves the high profile teams like the Yankees, and “steams” their lines, although not so much anymore.

      I really have no idea about the managers. Looking at the data, it sure looks that way. Plus there might be something about the organizations. I’m starting to believe that there might be.

      Keep in mind that much of the differences between my numbers and the actual ones are the over-regressing I am doing. It would be better for me to correct for that and then compare. The Vegas lines should be free of that bias, so comparing to the Vegas lines might be a better way of seeing how much each team has under or over-performed the “consensus” of the value of the team. Of course you have the “cheating” problem with the Vegas line too. So this was more of a first crack and a toy then a rigorous research piece.

      How long did it take me? A v-e-r-y l-o-n-g time!

  3. Tim says:

    Another thing (not to comment bomb) but, based on actual WP, your WP was “better” than vegas 9 times, “worse” than vegas 5 times, with one push. Considering you used Pinnacle (very sharp book), this is pretty neat stuff.

    I’d like to see you crystal ball for 2014!

    • MGL says:

      And you have to consider the Vegas “cheating!”

      I could do a RMSE for each game between my expected WP and the actual result of the game, using a pythagorean estimate from the runs scored in the game, and then do the same for Vegas. I don’t want to embarrass Vegas though!

      Release of my 2014 crystal ball will have to wait until AFTER the 2014 season!

      Feel free to comment all you want!

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s