Managing the Direction
Yesterday both manager of the year awards were handed out. Coincidently I was reading BP's Between the Numbers book just before the news broke, specifically the chapter written by James Click about evaluating Joe Torre's career. BP attempted to judge managers using the things they had control over; bullpen usage, playing time, and in-game strategy such as intentional bases on balls, sacrifice hits, and stolen base attempts. This sparked my idea on how to judge managers.
Before I begin explaining the method and give the results I want to strongly disclaim these statistics are hardly perfect (in fact the entire thing is quite flawed) however I'm presenting this is a "general idea" rather than a "definite" or "near definite". There are other aspects of managing that I'm clearly ignoring, and you will have to fill those blanks in, unless I go through each team and study the situations and playing time intently. The aspect I will focus on is the last part, IBBs, SHs, ect.
After collecting the mass numbers I ran linear weights on them, with one exception; turning the IBB value into a negative, because remember I'm not weighing team B walking team A's hitters, but rather team A's manager walking team B's hitters. That leaves us with the following formula:
(SBs*0.193)+(CS*-0.282)+(SH*-0.09)+(IBB*-0.176) = Managerial runs created.
| TEAM | SB | CS | SH | IBB | lwSBA | lwSH | lwIBB | LWTS | Wins |
| Boston | 120 | 35 | 28 | 17 | 13.29 | -2.52 | -2.992 | 7.778 | 0.7778 |
| Tampa Bay | 142 | 50 | 23 | 29 | 13.306 | -2.07 | -5.104 | 6.132 | 0.6132 |
| LA Angels | 129 | 48 | 32 | 32 | 11.361 | -2.88 | -5.632 | 2.849 | 0.2849 |
| NYA | 118 | 39 | 31 | 37 | 11.776 | -2.79 | -6.512 | 2.474 | 0.2474 |
| Philadelphia | 136 | 25 | 71 | 64 | 19.198 | -6.39 | -11.264 | 1.544 | 0.1544 |
| NY Mets | 138 | 36 | 73 | 53 | 16.482 | -6.57 | -9.328 | 0.584 | 0.0584 |
| Oakland | 88 | 21 | 30 | 45 | 11.062 | -2.7 | -7.92 | 0.442 | 0.0442 |
| Colorado | 141 | 37 | 90 | 49 | 16.779 | -8.1 | -8.624 | 0.055 | 0.0055 |
| Milwaukee | 108 | 38 | 54 | 32 | 10.128 | -4.86 | -5.632 | -0.364 | -0.0364 |
| Kansas City | 79 | 38 | 32 | 15 | 4.531 | -2.88 | -2.64 | -0.989 | -0.0989 |
| Seattle | 90 | 32 | 36 | 37 | 8.346 | -3.24 | -6.512 | -1.406 | -0.1406 |
| Cleveland | 77 | 29 | 43 | 28 | 6.683 | -3.87 | -4.928 | -2.115 | -0.2115 |
| Texas | 81 | 25 | 37 | 44 | 8.583 | -3.33 | -7.744 | -2.491 | -0.2491 |
| Minnesota | 102 | 42 | 52 | 38 | 7.842 | -4.68 | -6.688 | -3.526 | -0.3526 |
| LA Dodgers | 126 | 43 | 64 | 58 | 12.192 | -5.76 | -10.208 | -3.776 | -0.3776 |
| Toronto | 80 | 27 | 48 | 42 | 7.826 | -4.32 | -7.392 | -3.886 | -0.3886 |
| Baltimore | 81 | 37 | 27 | 44 | 5.199 | -2.43 | -7.744 | -4.975 | -0.4975 |
| St. Louis | 73 | 32 | 71 | 21 | 5.065 | -6.39 | -3.696 | -5.021 | -0.5021 |
| Pittsburgh | 57 | 19 | 66 | 31 | 5.643 | -5.94 | -5.456 | -5.753 | -0.5753 |
| ChicagoN | 87 | 34 | 65 | 45 | 7.203 | -5.85 | -7.92 | -6.567 | -0.6567 |
| ChicagoA | 67 | 34 | 28 | 42 | 3.343 | -2.52 | -7.392 | -6.569 | -0.6569 |
| Houston | 114 | 52 | 57 | 53 | 7.338 | -5.13 | -9.328 | -7.12 | -0.712 |
| San Fran | 108 | 46 | 57 | 59 | 7.872 | -5.13 | -10.384 | -7.642 | -0.7642 |
| Arizona | 58 | 23 | 68 | 41 | 4.708 | -6.12 | -7.216 | -8.628 | -0.8628 |
| Florida | 76 | 28 | 49 | 66 | 6.772 | -4.41 | -11.616 | -9.254 | -0.9254 |
| Washington | 81 | 43 | 64 | 44 | 3.507 | -5.76 | -7.744 | -9.997 | -0.9997 |
| Cincinnati | 85 | 47 | 72 | 40 | 3.151 | -6.48 | -7.04 | -10.369 | -1.0369 |
| Detroit | 63 | 31 | 30 | 63 | 3.417 | -2.7 | -11.088 | -10.371 | -1.0371 |
| Atlanta | 58 | 27 | 69 | 61 | 3.58 | -6.21 | -10.736 | -13.366 | -1.3366 |
| San Diego | 36 | 17 | 59 | 61 | 2.154 | -5.31 | -10.736 | -13.892 | -1.3892 |
After I accumulated the data, I talked with Peter and Sky about actually using it. My biggest concern (as well as theirs) was the lack of context in these numbers. The abundance of negative numbers is to be expected, after all the only way managers can "gain points" in this measurement is by having a successful stealing team, and even that is part luck. After some more discussion, I arrived at this "solution": using Baseball-Reference's "high leverage" splits for pitching and offense to compile the numbers. I did so, and let me just inform everyone I now know every team B-Ref's tag, fun!
Here are the numbers in high leverage situations:
| TEAM | SB | CS | SH | IBB | lwSBA | lwSH | lwIBB | LWTS | Wins |
| Boston | 32 | 6 | 14 | 9 | 4.484 | -1.26 | -1.584 | 1.64 | 0.164 |
| NYA | 38 | 8 | 16 | 19 | 5.078 | -1.44 | -3.344 | 0.294 | 0.0294 |
| Seattle | 29 | 7 | 16 | 12 | 3.623 | -1.44 | -2.112 | 0.071 | 0.0071 |
| Philadelphia | 42 | 6 | 30 | 22 | 6.414 | -2.7 | -3.872 | -0.158 | -0.0158 |
| NY Mets | 42 | 4 | 34 | 25 | 6.978 | -3.06 | -4.4 | -0.482 | -0.0482 |
| ChicagoA | 21 | 8 | 13 | 8 | 1.797 | -1.17 | -1.408 | -0.781 | -0.0781 |
| Minnesota | 23 | 10 | 8 | 11 | 1.619 | -0.72 | -1.936 | -1.037 | -0.1037 |
| Tampa Bay | 44 | 21 | 9 | 16 | 2.57 | -0.81 | -2.816 | -1.056 | -0.1056 |
| Houston | 35 | 13 | 26 | 14 | 3.089 | -2.34 | -2.464 | -1.715 | -0.1715 |
| Milwaukee | 29 | 9 | 30 | 13 | 3.059 | -2.7 | -2.288 | -1.929 | -0.1929 |
| LA Dodgers | 35 | 10 | 21 | 26 | 3.935 | -1.89 | -4.576 | -2.531 | -0.2531 |
| St. Louis | 18 | 10 | 16 | 10 | 0.654 | -1.44 | -1.76 | -2.546 | -0.2546 |
| Baltimore | 26 | 10 | 12 | 21 | 2.198 | -1.08 | -3.696 | -2.578 | -0.2578 |
| LA Angels | 34 | 13 | 28 | 17 | 2.896 | -2.52 | -2.992 | -2.616 | -0.2616 |
| Pittsburgh | 25 | 4 | 39 | 16 | 3.697 | -3.51 | -2.816 | -2.629 | -0.2629 |
| Arizona | 18 | 5 | 34 | 10 | 2.064 | -3.06 | -1.76 | -2.756 | -0.2756 |
| Cincinnati | 31 | 12 | 32 | 15 | 2.599 | -2.88 | -2.64 | -2.921 | -0.2921 |
| Kansas City | 17 | 10 | 24 | 7 | 0.461 | -2.16 | -1.232 | -2.931 | -0.2931 |
| Cleveland | 18 | 7 | 29 | 11 | 1.5 | -2.61 | -1.936 | -3.046 | -0.3046 |
| Oakland | 24 | 8 | 20 | 23 | 2.376 | -1.8 | -4.048 | -3.472 | -0.3472 |
| Florida | 21 | 6 | 24 | 22 | 2.361 | -2.16 | -3.872 | -3.671 | -0.3671 |
| Colorado | 37 | 16 | 43 | 14 | 2.629 | -3.87 | -2.464 | -3.705 | -0.3705 |
| Toronto | 21 | 4 | 30 | 23 | 2.925 | -2.7 | -4.048 | -3.823 | -0.3823 |
| San Fran | 45 | 18 | 32 | 26 | 3.609 | -2.88 | -4.576 | -3.847 | -0.3847 |
| Texas | 23 | 10 | 21 | 22 | 1.619 | -1.89 | -3.872 | -4.143 | -0.4143 |
| ChicagoN | 31 | 11 | 31 | 29 | 2.881 | -2.79 | -5.104 | -5.013 | -0.5013 |
| Atlanta | 17 | 7 | 28 | 23 | 1.307 | -2.52 | -4.048 | -5.261 | -0.5261 |
| San Diego | 14 | 7 | 28 | 20 | 0.728 | -2.52 | -3.52 | -5.312 | -0.5312 |
| Detroit | 11 | 9 | 22 | 23 | -0.415 | -1.98 | -4.048 | -6.443 | -0.6443 |
| Washington | 22 | 15 | 32 | 25 | 0.016 | -2.88 | -4.4 | -7.264 | -0.7264 |
Boston again rates at the top. Many broadcasters talk Terry Francona up as a great manager, but for all the wrong reasons. I am sure he is a nice person, and the players like him, yet the guy is a pretty good strategist if you believe these numbers. It doesn't hurt having great personnel and an outstanding front office either. Joe Girardi's high leverage non-personnel tactics are absolutely fine. Amusingly, so were the combination of John McLaren and Jim Riggleman. That's one of those situations where the personnel is the issue. Atlanta, San Diego, Detroit, and Washington again rank low, perhaps Bobby Cox's best is behind him?
Interestingly both of the World Series teams finish within the top 10 on both scales, but Joe Maddon becomes far worse in high leverage situations, unfortunately his worst habits seemed to follow him into the World Series, as MGL covered nicely here. Even still Maddon's regular season methods fell secondary to Francona's in both instances, although his team did win more games, but you know how processes are more important than results in the long-term.
Here's a look at the averages:
| Team | NonLvg | Lvg | Avg |
| San Diego | 30 | 28 | 29 |
| Detroit | 28 | 29 | 28.5 |
| Atlanta | 29 | 27 | 28 |
| Washington | 26 | 30 | 28 |
| San Fran | 23 | 24 | 23.5 |
| Florida | 25 | 21 | 23 |
| ChicagoN | 20 | 26 | 23 |
| Cincinnati | 27 | 17 | 22 |
| Arizona | 24 | 16 | 20 |
| Toronto | 16 | 23 | 19.5 |
| Texas | 13 | 25 | 19 |
| Pittsburgh | 19 | 15 | 17 |
| Houston | 22 | 9 | 15.5 |
| Cleveland | 12 | 19 | 15.5 |
| St. Louis | 18 | 12 | 15 |
| Baltimore | 17 | 13 | 15 |
| Colorado | 8 | 22 | 15 |
| Kansas City | 10 | 18 | 14 |
| ChicagoA | 21 | 6 | 13.5 |
| Oakland | 7 | 20 | 13.5 |
| LA Dodgers | 15 | 11 | 13 |
| Minnesota | 14 | 7 | 10.5 |
| Milwaukee | 9 | 10 | 9.5 |
| LA Angels | 3 | 14 | 8.5 |
| Seattle | 11 | 3 | 7 |
| NY Mets | 6 | 5 | 5.5 |
| Tampa Bay | 2 | 8 | 5 |
| Philadelphia | 5 | 4 | 4.5 |
| NYA | 4 | 2 | 3 |
| Boston | 1 | 1 | 1 |
It's tricky using these as is, but only a single seasons worth of data likely isn't worth much either. That's why I'm disclaiming the heck out of this and hoping people take it with a grain of salt, it's only a part of what managers do, and it's a rough attempt at quantifying that part.
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6 comments
Comments
We love Tito
He can be a dumbass at times, but he’s great.
Manager of the Year is a really dumb award. They just give the award to the team with the most wins or best story…
Mother---- him and John Wayne!
by MerryGoByeBye on Nov 13, 2008 12:45 PM EST reply actions 0 recs
No surprise at Bobby Cox
Legendary motivator. But not a good strategist.
Is there any way for you to factor in bullpen usage? I feel that’s pretty significant. Well, actually I have Baseball Between the Numbers. I should probably start by rereading that chapter. I just remember the conclusion there was pretty much that good managers don’t really affect things that much while bad managers can really screw things up.
by VictorW on Nov 13, 2008 1:45 PM EST reply actions 0 recs
I'm not sure how we could implement it in a timely matter.
Because a large part is whether Pitcher A is really better than Pitcher B in certain situations, and from there not only are you talking about context, but super context.
by R.J. Anderson on Nov 13, 2008 1:54 PM EST up reply actions 0 recs
Maybe something comparing relievers' tRA to LI?
That would be a decent way to see if managers were properly leveraging their relievers. LOOGYs might present a problem, though.
Beyond the Boxscore // Calling BJ Upton lazy is lazy.
by Sky Kalkman on Nov 13, 2008 3:04 PM EST up reply actions 0 recs
As I discussed with RJ, context is a big issue here.
IBBs can be good ideas and they can be bad ideas. The break-even point for SBs drastically changes between situations. Same with sac hits.
While this might not be a great measure of managers, it does describe their styles pretty well. I like seeing who IBBs a ton and who sacrifices a lot.
Beyond the Boxscore // Calling BJ Upton lazy is lazy.
by Sky Kalkman on Nov 13, 2008 3:24 PM EST reply actions 0 recs
good effort, keep it going
I know much more work can be done in this area concerning evaluating ML managers. It’s a very interesting subject that needs more examination.
A ball player's got to be kept hungry to become a big-leaguer. That's why no boy from a rich family ever made the big leagues. ~Joe DiMaggio, quoted in New York Times, 30 April 1961
by kdog on Nov 14, 2008 12:04 AM EST reply actions 0 recs

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