Having a summary opinion without evidence is bullish!t. – Tom Tango
The above quote illustrates why I enjoy Tango’s work. Everyone has an opinion — what’s the old saying? — and they’re entitled to that. But that doesn’t mean we should take every opinion seriously. Only opinions backed by argument, based on facts and a logical thought process, warrant consideration. So when a fairly prominent blogger tries to stir the pot by deriding the sabermetric community, using little or no evidence, Tango will likely respond.
We’re no strangers to Mike Silva. We’ve addressed at least one of his evidence-less rants, and see plenty more of him on the BBTF Newsstand. In the traditional talk radio style, he makes emotional appeals as a substitute for evidence, but that type of argument doesn’t fly in statistically inclined baseball communities. We require evidence.
Proving that he’s not 100 percent gasbag, Silva agreed to send Tango 10 questions about advanced statistics and the sabermetric community. Before linking to the entire series, I’d like to note some highlights.
My biggest beef with Silva — the reason I no longer visit his site — is his stance on the sabermetric community. He suggests that “the ultimate goal is to mainstream their theories and perhaps gain more power in the baseball community.” Using “mainstream” as an infinitive peeves me enough, but the idea that statistically inclined fans want to gain more power is preposterous. Tango rightfully takes Silva to task on this issue, though his focus is more on the second part of Silva’s non-question, wherein he claims that “the ‘value’ of hose these metrics can be used seems to be marginal in my opinion.” Tango:
It’s one thing to say that you don’t understand it, so either you accept it or want to learn more or ignore it. It’s another thing to say that you don’t understand it, and so you will dismiss it as being “marginal” or worse. You have no basis for dismissal. Ignore it, if you must. Dismissing it is out of the question. There’s a huge number of people that find value in it.
Another interesting sequence arises when Silva asks about the future of sabermetrics. Where will we see advanced metrics in 10 years? “Fad? Major part of a front office operation? Replace traditional scouting?” No, yes, and no are the correct answers, but Tango takes it a step further.
You haven’t seen anything yet. Wait until PITCHf/x, FIELDf/x, and HITf/x take shape. You will wish and pray to get back to the simpler times of 2000s. The 2010s will bring an avalanche of data. It will absolutely be a major part of the front office. The best-case scenario is that you have all these f/x systems set up at colleges and high schools. Instead of one scout seeing one game of some prospect in one town, while missing a game on another town, you will have every single pitch charted, every swing charted, and every single fielder charted. The question is to try to identify all of the contributions of each player to each pitch and each play. Having a summary opinion without evidence is bullsh!t. Scouts have summary opinion on limited amount of data (say they see 5% of someone’s games in college). That’s valuable. Now, imagine having a summary opinion based on 100% of the data?
I think this describes what happened after I read that paragraph.
I also enjoyed Tango’s explanation of FIP. I think this point is lost on many proponents of the stat: “it is only concerned with one component to pitching. And that component is the one that does not involve his fielders.” It’s like OBP, and Tango makes that connection as well. It tells us just one thing. It happens to be a very important thing, but there are other factors to consider, just as we consider factors like power and base hits when discussing OBP.
If you have questions about sabermetrics yourself, or you just want to see Tango dole out some quality arguments and explanations, I recommend the entire series. It’s not an overly long read, and I think it’s totally worth the time.
Part 1: UZR
Part 2: WAR
Part 3: WAR and finances
Part 4: FIP
Part 5: Stat saturation
Part 6: The goal of sabermetrics
Part 7: Selling the stats
Part 8: Hall of Fame
Part 9: Stats in fantasy baseball
Part 10: The future