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Statistical analysis and the Twins: together at last?

Last offseason during an appearance on KFAN radio, I commented that the Twins were one of the increasingly rare MLB teams without any sort of department focused on statistical analysis. Assistant General Manager Rob Antony brought up my comment in an interview a couple days later and noted somewhat tersely that the Twins’ decision-makers did use stats, but in doing so pointed to OPS, home/road splits, and other fairly mainstream, publicly available numbers.

My point was never that the Twins ignored all stats, because that has likely never been true of any front office, ever. My point was that for better or worse, they didn’t employ the advanced statistical tools that have become available recently and are in fairly wide use across MLB. In other words, I wasn’t talking about OPS or home/road splits. I was talking about PitchFX data, play-by-play defensive metrics, and other info the average fan can’t find in 30 seconds online.

In an effort to clear the air and get some clarification, I sent Antony an e-mail and he was nice enough to respond with an explanation of the Twins’ stance on the issue, which made it pretty obvious to me that they indeed did not have a department devoted to statistical analysis and were not using the types of advanced tools to which I was referring. All of which brings me to an interview Antony recently did with “Over the Baggy” blogger Parker Hageman.

Like me, Hageman is very interested in the growing world of baseball analysis and data, so the interview focused on the Twins’ involvement in those areas. Antony shared tons of great info, including the fact that the Twins “just hired a guy whose sole focus is statistical analysis.” He added: “Gathering information and creating databases. This will be his first year. The guy that we brought in will start creating systems to build a foundation of our own that we can look at.”

Obviously the success of such a system depends on the people involved and how much weight the front office gives the analysis being presented, but that’s precisely what I had in mind last winter, and I’m thrilled to hear the Twins have finally hopped on board. And despite his publicly disagreeing with my statements back then, Antony admitted to Hageman that “we’re probably one of the last, if not the last, team to address it with a person dedicated solely to that.”

Better late than never, for sure, although several of Antony’s other responses in the interview suggest that the newly hired stat guy will definitely have his hands full getting his voice heard or perhaps even understood. Antony made a number of worthwhile points regarding the limits of statistical analysis and how the Twins have succeeded without it, but also showed what is to me at least a startling lack of knowledge on the subject for an assistant general manager.

For example, when asked if he knew what the statistic FIP stands for Antony said that he “just saw this one the other day” and guessed “first strike in inning pitched.” The answer is Fielding Independent Pitching, and both the FIP stat and the analysis behind it have been around for years. Similarly, he didn’t know that BABIP stands for batting average on balls in play, which is a fairly basic concept and one of the building blocks of statistical analysis.

Whether or not the Twins actually use or even value stats like FIP or BABIP, it shocks me that the assistant GM isn’t at least aware of and reasonably familiar with them. As for what stats he does make use of, Antony explained that the Twins “look at a lot of home/roads splits” and “we’re big on OPS, we’re big on WHIP” while admitting that those are “traditional things that I know people have gone beyond and gotten deeper.”

Antony provided a couple of specific examples to further hammer that point home, describing Nick Blackburn‘s potential for improvement as “instead of being an 11-11 guy, we believe he could easily be a 15-9 guy” and saying that he’d “rather sign a guy” with a high RBI total than a high slugging percentage “because you win with runs.” Evaluating hitters on their RBI totals and pitchers on their win-loss records shows how being so behind the times impacts decisions.

I’m certainly not suggesting that the Twins must become a stat-driven front office — they’ve had plenty of success on their own terms and are coming off a particularly strong offseason — but I am suggesting that being legitimately involved in the expanding universe of statistical analysis would be beneficial to their long-term outlook, and it’s disheartening to hear how little they’ve dipped their toes into that water so far.

Hiring a stat guy is a big step in the right direction and one that Antony and company deserve credit for taking, but even if he does a terrific job crunching numbers, creating databases and presenting valuable analysis, he faces an uphill battle to make a big impact in an organization that’s a decade slow to adapt. Hopefully the front office has an open mind, because the Twins’ scouting and development, combined with some new-school views, could be a beautiful thing.

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Comments (2)

  1. Submitted by Jim Meyer on 04/02/2010 - 10:15 am.

    Aaron
    I enjoy your columns, even if I don’t always understand them. I am merely curious why you feel BABIP is such a superior metric. I guy could strike out a ton but spray a bunch of singles and bloops all over and his BABIP could be miles higher than his basic average. Basic batting average is a lacking stat for you? Really? I know some .300 batting averages are better than others, but really? BABIP?

    About this XFIP. Can I buy a hyphen and stick it between Fielding and Independent. Or change this stat to xERA – D(efense), or F if we are really talking about Expecting Pitching Independent of Fielding.

    Yes, the Twins should probably engage the innovations of their craft, but I’d be more concerned if I were convinced of the gadgets’ value.

  2. Submitted by Dave Eldred on 04/05/2010 - 08:54 am.

    Jim, BABIP actually solves the problem you identify. If you see a guy with a sky high BABIP — .350, for example — it is most likely the product of luck, and you can expect him to regress to the mean.

    Batting average does NOT identify those players. You state that some .300 BAs are better than others, but looking at BA alone, you can’t figure out which ones are good and which aren’t. BABIP actually helps solve the problem you identify, whereas BA does not.

    There is no stat that is perfect, and no one is suggesting that teams abandon scouting. However, why wouldn’t you want to know everything you possibly can about your players and players you hope to acquire? It is silly that the Twins have ignored advanced statistics for so long. It’s a relatively inexpensive tool to add to the arsenal.

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