Here, the announcer has identified the situation (measuring defense with errors) and the problem (errors don’t accurately portray defense), but he won’t take that next step (what do we do about this? why is this significant?). This is significant because the problem causes fans to improperly identify good fielders. What we do about this is find a better way to measure defense, and what do you know, we have a few in UZR, Dewan’s +/-, and Defensive Efficiency (among others). One might argue that the man in question has never seen or been exposed to these new statistics, but the man in question worked with Boog Sciambi for the past few years. If you don’t know who Sciambi is, he is a wonderful broadcaster that tried to integrate new statistics into a certain team’s telecast, and he did so effectively. The announcer knew about these statistics, but he has apparently ignored them and rid them from his mind.
I’m probably preaching to the choir a little bit here, but I will get to the point in a minute. The announcer does a good job of identifying the problems with errors (weird bounces that aren’t a player’s fault, the blurry line between hits and errors, scorer’s judgment, etc.). The next step is to find a solution. There’s more to defense than errors. It’s more about making plays on balls in play. If Player A and Player B are given 100 identical plays, you want the guy who makes the play the most number of times. The number of errors doesn’t matter because they are simply counted within the number of plays not made. Let’s say Player A makes 75 of those plays and has 6 errors, and Player B makes 70 plays and has no errors. Which player do you want at that position (believing that they represent equal offensive value)? Player A because he makes more plays (converts more balls in play into outs) than Player B. The errors do not take away from the number of plays made because, as I said, they simply count as a play not made.
Of course, the world doesn’t work so neatly for us, but that’s why we have UZR, +/-, etc. They go through and try to track the number of plays made vs. the ones that should have been made or would have been made by an average defender. We can argue over which one to use or if they are perfect, but one cannot argue that errors evaluate defense better than any of them (I guess you can argue that, but I don’t think it’s an argument you’re likely to win). Stats people smarter than I will continue to work out the kinks on the new metrics (Field f/x is pretty exciting), but the newer statistics include errors and go further.
Anyway, again, I might be preaching to the choir, so let’s get on with it. In the battle between sabermetricians and traditionalists (and it is a battle, with words – often insulting –, being flung instead of bombs), I believe a common misconception is that traditionalists don’t understand what’s wrong with regular statistics and that they’re ignorant. I actually think they do see the problems. Fans, announcers, reporters, etc. continually contextualize those stats (errors that didn’t deserve to be, line drives that don’t fall in but hurt batting average, bloop hits that score runs hurting a pitcher’s ERA, etc.), and they, then, quasi-scientifically compensate (“Well, I’m not sure that was an error, so we’ll just ignore that one”). The problem with that is that it’s highly subjective (what is an error?), it overlooks a few things (would someone else have made that play more easily, for example), and that mental note is often forgotten (“He made 20 errors! He’s horrible,” while forgetting that 4 or 5 of those were “questionable”) which then equates that semi-error with all the other legitimate errors. People try to do the mental math, but the actual math has already been done for them.
And please do not take this as an attack if you happen to be a “traditionalist” (I hate labels like this because it directly associates a person with a group to which they may have little to no allegiance). I am genuinely curious. What causes this disconnect? What is the part of the bridge that hasn’t been built yet? Because I think the problem is more social science than strictly scientific. I think people do understand the logic behind newer statistics, but they still refuse them. Is it fear that they will show your favorite team/player isn’t what they seem? Is it the reluctance to admit you were wrong in the past? Is it the source of the new statistical movement (a man I very much respect has some issues coming to the “Dark Side” because he finds it difficult to get past Keith Law’s prickly nature)? Is it a lack of exposure?
What causes someone to ignore the answer that seemingly stares them in the face? What causes someone to not realize that they’re even asking the question?