Do Catchers Really Make the Best Managers?

Those are some interesting stats dug up by Glenn Berggoetz and Jeff McBride. I am wondering though, does it also include interim managers as well?

I don't know about the charts, but the overall Catcher WP goes up to about .491. Not a big jump. Mack had about 10% of the manager seasons, but he wasn't really THAT far below the average. He may have affected the longevity numbers, but probably not much else.

I think that what be a better indicator is comparing the actual winning percentage of the teams' of catchers to their Pythagorean Winning Perecentage (Runs scored [squared] / (Runs scored [squared] + runs allowed [squared]). This might make up for the possibility that catchers have just had worse teams.

Much ado about nothing. In the history of the game, every single position have won between 49 and 51% of the games they have later managed. That was an awful lot of math to show that you'll win about 50%, and position has nothing to do with it.

See, this is where my statistical analysis starts to fail me. I THINK what needs to be done is to find a way to compare how a team did under certain types of managers, and then see if the difference is greater than what would be expected by chance alone. For example, I think there's a concept like "expected variance" for a set of data. Take the winning percentage tables shown first. (I'm going to start making numbers up here now, just to try to explain what I'm thinking of). For the data considered, the expected standard deviation (related to variance) of the data might be something like .005. Or it could be something like .05. If it's .005, than every category between .505 and .495 is within the range that chance would explain, so we can't say that there is a statistically significant advantage to those. LF, 1B and Catcher, on the other hand, are statistically significant, and would suggest that catchers actually make bad managers, and the other two make generally good managers (obviously the difference over a long time might be slight, but who knows). If it's .05, then all of this is just noise that falls inside of chance, and the previous poster is right, that it doesn't make a lick of difference who you hire. If it's much lower, than all the data might be valid, and the ranking is actually useful.

If what I'm saying is making any sense to someone with a better grasp of statistical analysis, let me know, because I have a feeling that I'm on to something, but I have no idea how to calculate that "expected variance" (partly because I don't have the full data). And if i'm totally talking out of my ass, let me know that too. =)

I was thinking the same thing as Eric, perhaps catchers just haven't had good teams to manage compared to others. Which could make some sense even without dealing with any numbers.

Think of it like this - people believe catchers make better managers, so when they have a terrible bunch of players, they'll likely think they can help their team by hiring a former catcher to manage the team.

There's something else I'm wondering. Perhaps catchers improve a team quicker than other positions? That could be interpreted in the mind as a manager doing much better, even if over the long run he does worse. Basically, it's about first impressions.

Taking a different approach, I think that Cs might be seen as good managers because they lie somewhere in the middle of pitchers and players. This is like wanting to not hire an offensive coordinator or defensive coordinator in football -- the ideal is someone who is proficient at both. While Cs can't pitch, they are closer to having mastery at that position than, say, a LF.
Along the same lines, a C has to know both offensive schemes (e.g., "this guy is likely to bunt here") and defensive schemes (e.g., "we need to move in 3B because this guy is about to bunt"). Compare that to a LF, who needs to know how shallow to play and when to back up the bases (e.g., "my catcher is going to overthrow third on this steal attempt").
Sure, the manager can relay all that information to either LF or C, but I think less so to the latter.

There are two big problems with this study: one is that the sample sizes are far too small. The second is that they assume all teams are of equal quality, which is demonstrably not true.

In reference to Ali Nagib's comment about standard deviations. If you take all winning percentages across managers (despite the position they played) and calculated their deviations from the mean winpct. (called amazingly, 'standard deviation') you'll have a metric that allows you to make assumptions about the distribution of the data assuming it's bell-shaped. For example, if the mean value of winpct. is 0.50 and the standard deviation is 0.01 (and the sample size is sufficiently large) we can make the following claims about statistical significance:

* We're 95% confident that winpct. values between 0.48 and 0.52 are statistically the same. Basically there is no (statistical) differenc between any winpct. falling in this range. So if the actual standard deviation of these winpct. data are indeed 0.01, then we can be pretty sure that Catchers as managers are no worse than LFs as managers (at least statistically).

*Why is the range 0.48 to 0.52 if the standard deviation is 0.01? Because in statistics there is something called the empirical rule that states, "95% of all observations fall within 2 standard deviations of the mean"

See, that's what I thought, but I wasn't totally sure that SD alone was the answer. For some reason, in the back of my head, I had the idea of "expected SD" vs. actual SD rolling around, and I couldn't remember how to get the two to jive. Anyway, if the guys who did the anaylsis see this, I'd like to see what they come up with in reference to this. I have a feeling (just a feeling) that SD goes down as the sample size increases, meaning that it could actually be awfully low, like .001 or something. If that's the case, than just about all the data is significant. But I could be wrong.

Interesting study, but I think there are some confusion on the premises. Although it's often stated, by TV announcers, that catchers make the best managers, I doubt that's what they actually meant. What they probably mean is that "catchers are more inclined to go into coaching, and due to their famaliarity with both sides of the game, it is easier for them to become good at it."

The difference is subtle, but obvious. Put it another way. Teams don't just go out and pass out coaching trials to any washed up catcher because they think he will make a great coach. The retired players, regardless of their previous playing lives, have to want to coach. And you are more likely to pursuit something if you know more about it. Thus, it's possible more catchers and middle infielders are interested in coaching than, let's say, a closer like Mitch Williams, and have an easier transition from playing to coaching.

On the other hand, I think there is an intuitive explanation about why catchers on average do worse than others. It's related to sample size. I would bet there are more catchers than other position players in coaching. As the sample size increases, you are more likely to regress to the mean. On the other hand, players from other position may be lucky or may be harder working (as a way to fight against the so called "myth"). My analogy in another sport would be Spud Webb in basketball. Because of his disadvantage in height, he probably had to work harder at his skills/craft. On average, I bet he and Mugsy Bogue probably had better careers than the average NBA player. But that does not mean the NBA teams should go out there and draft only players under six feet. Taller is better. Again, it's a two-way street. You will never be good at something if you believe in "innate" talent, and don't work hard at your game.

Berggoetz and McBride find the reason for this phenomenon when they say, "pitchers are routinely overlooked for managing posts ... and are fired sooner while winning more often." If two managers of exactly the same skill take over two equally good teams, and lead them to the exact same record, the catcher has less of a chance of being fired than the pitcher. So overall, a pitcher needs to be a better manager to overcome the anti-pitcher bias, while a catcher who manages poorly may get away with it. This leads over time to the stats that Berggoetz and McBride found.

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