Baseball continues to fascinate me. Each year, we learn more about how to properly evaluate what we see with our eyes. Still, we often struggle to understand just how well certain players perform in a given season. And I’ve struggled with something all year in regards to evaluating the Reds players. We’ve come a long way in more accurately depicting a player’s offensive value in regards to run scoring; we still labor to properly evaluate defense.
Defense is hard to evaluate because of all the variables involved. For instance, suppose a ball is hit three steps to the shortstops right a total of fifteen times. One shortstop fields the ball ten times and makes ten outs. Another shortstop fields the same ball 14 times, makes two throwing errors, but gets twelve outs. The latter player has more errors but actually converted more plays into outs. We don’t like the errors, but the two extra outs mean quite a bit.
And that is the essence of evaluating defense. The best defensive players convert more plays into outs. So, if there were some way to measure how often players of a certain position make a particular play, we could determine which players make more outs than others.
Currently, the two most popular systems for evaluating defense on an advanced level is defensive runs saved (DRS) and Ultimate Zone Rating (UZR). These two systems work similarly with some slight differences.
I’m not going into all the math. I don’t like math. Me teach writing. Numbers bad. Words good. So, I’ll give you the basic idea of how these systems work.
Both systems measure how many runs above or below average a player is worth based on position. As we will see in a minute, Todd Frazier has a DRS of 6, meaning that he has saved six more runs this season than the average third baseman. UZR has him at 6.9, which means essentially the same thing only with decimals.
On these scales, 0 is average. As a rule of thumb, Fangraphs lists the following tiers for DRS and UZR has the exact same scale:
Both systems use human evaluators that watch EVERY PLAY of every game. These evaluators identify where a ball is hit and calculate how long it takes the ball to reach that area of the field. Based on years of analyzing video and collecting data, evaluators can calculate how often a play is made by a fielder.
So if a ball is hit down the line, we can calculate how quickly that ball gets into that zone (DRS uses timer data) and find out from years of data that the third baseman makes that play 20% (made up number for the illustration) of the time.
If Todd Frazier makes that play, he is credited with .80 points or 1.00-.20. If he fails to make that play, he is credited with -.20 points. It doesn’t matter if the player had to dive to make the play, or if he had enough range to make the play look routine. Either way, the play is scored the same because the ball was hit in the same area and got there in a similar time frame.
Evaluators then use a lot of math and historical data to turn this information into the theoretical runs saved that both systems use. While this system makes up a large part of the evaluation, there are other factors. An outfielder also creates outs with his arm. Not only do outfielders throw out runners, but runners will run less frequently on a player who has a good arm and keeping a runner from advancing a base has value. Errors, how often bunts are turned into an out or outs, ability to turn double plays, and others factor in. You can read more detailed information about UZR here and DRS here.
These systems are great. They take a little of the subjectivity out of defensive evaluation, even though people are still involved in the process. But in spite of their similarities, these two systems don’t always agree. In regards to the Reds, their key players have generally performed well in these two metrics. Here is some data.
This data exemplifies my confusion with these metrics: we can immediately see some discrepancies. In this case, three players have significantly different results. Billy Hamilton rates eight runs better by UZR. That’s a ton of value. If Hamilton is closer to a seven run defender, he isn’t even a starter. Certainly, not a very good one. If you are wondering why Hamilton’s fWAR (2.0) is so much bigger than his bWAR (0.8), it’s largely because Fangraphs uses UZR in their WAR calculation while Baseball Reference does not.
Brandon Phillips has dazzled with his defensive prowess once again this season. Yet, DRS has him as a very good defender while UZR has him as a slightly above average defender. The DRS system suggests that Phillips’ range hasn’t deteriorated much at all. UZR has Phillips’ range declining quite a bit over the last two seasons.
I can’t help but believe Phillips is closer to a very good defender than an average one. By DRS, he ranks as the seventh best defensive second baseman this season. That seems about right to me, maybe a few spots higher. UZR doesn’t have Phillips in the top ten. Hard to believe that guy isn’t a top ten defender at his position.
Jay Bruce also has about a five run difference in one measure than the other. Just like with Phillips, DRS rates Bruce more highly than UZR. By these measures, Bruce is either an above-average, top-ten rightfielder or an averagish corner outfielder. That’s a pretty big difference.
Bruce had an awful defensive series in Philadelphia earlier this season, but besides that, he has been solid defensively. Quite frankly, I think Bruce is still an above-average defender. He may have lost some range since knee surgery, but he still possesses a strong arm that keeps players from getting extra bases. Bruce has had a strong, if unspectacular defensive season.
The Reds haven’t done much right this year. But they have played strong defense. While these metrics are likely the best indicators of defense we have, no one is really convinced of their supreme accuracy, so take them with a grain of salt. But based on what we’ve seen this year and the metrics, they all seem like pretty good defenders with Hamilton being elite, Phillips still playing at a high level into his mid 30s, and Bruce returning to above-average form.