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Feb 252010

A little over a week ago, Moshe posted a piece asking if sabermetrics have gone too far. Since that time, after reading the article itself and various responses to it throughout the Web, I’ve been thinking of ways that could help bring sabermetrics into the mainstream.

Perhaps I’m being too ambitious here; after all, I’m just a blogger who’s not deeply embedded in the metric community, nor am I someone who’s involved in developing new stats and metrics. Regardless, I regularly use advanced metrics in my posts here, and I attempt to use them in conversation with other baseball fans (so far, I’ve only had one conversation of memory in which the other party was also versed in said metrics), so I’d like to see them become a little more popular.

Briefly touching on something Moshe discussed at length, I’ll say this: there are a ton of stats out there. The “market”, so to speak, may not be completely flooded, but the water level is rising. To some, like myself, there is an appeal to this. The more stats there are, the deeper I can delve into the game. The more stats there are, the more I can find out about the players I enjoy watching. To some, these advanced stats can be quite intellectually stimulating. To put a personal spin on things: I was awful at math all through school, elementary through undergrad. However, for some reason, I can grasp the theories and (sometimes) the procedures behind these stats. There is, though, a flip side to that coin. Some people are understandably put off by the amount and style of metrics out there. A sort of sensory overload occurs and the causal fan could be come very disinterested.

In my interactions with friends, family, and other fans on the internet, through reading various print and internet articles, there seems to have been a misinterpretation as to the object of metrics. It’s not to alienate older fans. It’s not to make it so that games are played on a spreadsheet from our mothers’ basements. The point of metrics is to inform and to entertain. We who use them do so to, as I said before, attempt to gain a better understanding of how the game works. For us, the metrics enhance our enjoyment of the game. The beauty of baseball is that each of the 162 games in the season is a different story. It’s like an every day soap opera with better performances and better lighting. Using metrics does not make us lose sight of that. The numbers we use just represent a different way to tell the same story. At the end of the day, that’s what all stats are: numerical representations of the games we watch and listen to.

So what can be done to make these numbers more accepted and widespread in mainstream baseball analysis and debate? First, the concept, or concepts, of each stat needs to be introduced. Starting with the broad aims and beliefs of the metrics makes understanding them much easier. So, instead of throwing FIP at you, I’d explain to you that it tries to measure the pitcher outside of his defense. While this is a bit abstract, it’s still easier to understand than it would be if I threw the formula for FIP at you. This helps to create a bit of a context for a hard-to-recognize number.

Creating a context for these stats is just a small part of making them more accessible. The biggest thing, though, that could be done to make these metrics more accessible is to do something simple (that’s already being done, really): make the scales familiar. Some stats already do this. For example, wOBA is on the same scale as OBP; EQA is on the same scale as BA; FIP is on a runs per nine innings scale, just like ERA. Though those stats are more complete–and slightly more complicated–than the typical stats, their scales make them easy to recognize and easy to comprehend. Hopefully, more metrics follow this model in the future.

Normalizing stats, that is, adding the ever awesome “+” at the end, is another technique that could help the casual fan become more engaged in advanced metrics. With some of these stats, especially ones like tRA, it’s hard to know what’s good and what’s bad. Luckily, there’s a tRA+–just like ERA+ and OPS+–to help us compare that number to the league average. Again, this helps to give the number context. Another new(er) stat that does this is Weighted Runs Created+ (wRC+). Any time we can quickly compare a stat to the league average, it’s incredibly helpful.

My last bit of “advice” is aimed more towards the causal fan: don’t worry about how exactly the stat is calculated. Just because a stat cannot be quickly calculated, or it takes more than a few steps, does not mean it is illegitimate. If a stat as convoluted as Quarterback Rating can be popular among NFL analysts and fans a like, there’s no reason a much less complicated stat, like wOBA, cannot become popular among mainstream baseball analysts and fans. The result of the calculation–the stat itself–is what matters most. If you can understand that answer and the concept behind it all, you’re in very good shape.

Obviously, these changes aren’t going to occur overnight. It will take a long time for these stats to be accepted into the mainstream. When they are, I’m sure there will be a whole new batch of metrics that will be knocking on the proverbial door to be let in. Regardless, this world of stats is ever changing and ever evolving. As writers, observers, and fans, we should be changing with it. So, I suggest to you–the ones who don’t get or don’t like these new metrics–give them a try. You never know, you just might like it.

8 Responses to “The Numbers Game”

  1. If you watch a lot of games, sober and without rose colored glasses, the new wave of stats are not very important.
    I didn’t need a lot of stats other then the obvious ones to recognize that Derek Jeter was still a very good SS and very good hitter with men on base and a guy that made productive outs.
    I don’t need fancy stats to see that Cano is a first ball hitter with no patience and can be suckered into swinging at bad pitches with men on base.
    I also didn’t need stats to know that TEX saved numerous, numerous games by making great plays at first base that GIambi would have allowed to turn into game changing doubles and that TEX was the best throwing first baseman that i have ever seen.
    Whether or not the stats confirm or don’t agree, watching the games tells the real story.
    Did anybody REALLY think Derek jeter was the worst SS in baseball before last season? RIdiculous.  (Quote)

    [Reply To This Comment]

    Matt Imbrogno Reply:

    Looking at stats is the same thing as watching the game. What happens in the game shows up in the stats.

    And, yes, before 2008-2009, Jeter was a very bad fielding shortstop. Watching the games could’ve told you this. He consistently had trouble getting to balls that were not hit directly at him. This year, his movement to his left improved vastly, but he’s still a little shaky on balls to the right. However, he was greatly improved in 2009 and was one of the top defensive SS’s in the league, as well as the finest hitting SS not named Hanley.  (Quote)

    [Reply To This Comment]

    Moshe Mandel Reply:

    I think that’s taking it a bit far. I think there are elements to the game that are in fact better comprehended by watching, and watching can also help you interpret some of the data. I wouldnt say looking at stats is the same as watching.  (Quote)

    [Reply To This Comment]

  2. Matt Imbrogno: Looking at stats is the same thing as watching the game. What happens in the game shows up in the stats.And, yes, before 2008-2009, Jeter was a very bad fielding shortstop. Watching the games could’ve told you this. He consistently had trouble getting to balls that were not hit directly at him. This year, his movement to his left improved vastly, but he’s still a little shaky on balls to the right. However, he was greatly improved in 2009 and was one of the top defensive SS’s in the league, as well as the finest hitting SS not named Hanley.  (Quote)

    i totally disagree.

    Jeter was ALWAYS brilliant on pop flies, covered more ground on them than any SS in baseball and was equally adept on the slow roller becuase he played shallow.to cut off the swinging bunt and always did.Additionally, he made the tag play, pivoted on double plays and handled cutoff throws and made the next throw as good as as any SS in baseball.
    If you play shallow it’s harder to reach balls, especially to the 2nd base side and Jeter has always gone in the hole and made the jump throw with the best of them.
    So, because of stupid new stats Jeter went from a gold glove winner to the worst SS in baseball and suddenly at age 35 became a gold glove winner again..
    Uh, no, Jeter played depeer last season and played with a better starting pitching staff and much, much better first baseman and that was most of the difference along with him being a bit healthier last season.
    I love people make up nonsense and the world runs with it.
    One year Jeter is a hall of fame all time great and the next year he’s over rated, doesn’t hit with power, can’t field etc. etc.
    Now he’s in decline until he bats .335 at age 38 and then the same guys will say Yankees will have signed him cheap.
    And, no watching the game closely and understanding what’s going on is idfferent than reading stats.
    If you look at Joe Namath’s or Sandy Koufax’s stats, maybe they aren’t HOF’ers but if you saw Sandy pitch and saw how he dominated baseball at such an unbelievable level you have no question he’s an all time great, same deal with Joe Willie when healthy, nobody ever played the position better, not even Unitas but his stats don’t tell that story.You needed to see them play.  (Quote)

    [Reply To This Comment]

  3. Matt, I think the common fan will realize the richness imparted by OPS, IsoP, and the common usage will expand to include them, as it has already OBP and WHIP. Serious fan-ning has always been a numbers game. Lefty-righty splits are undeniable intelligence, and many other points of interest carry a tale.

    More arcane indices may be useful, but one thing I ask: please liberally link to glossaries or otherwise drag your feet a bit with explanation amid your allusions. Your example above of FIP is most apt: somebody’s been fippin’ me off the last couple days, and when I looks it up, I see only walks and homers against are counted, whereas these jerks seemed to have been using it as a superior substitute for any other metric, as a general conveyance of pitching worth. I quit reading then, but I appreciate your mention of the purpose, a worthy distinction, if reliable.

    With regard to your “ever awesome” + and your cute little w’s, I would expect the common fan would find that a bit to hard to swallow, for now. Let me get used to OPS before you start scaling it. Why not use sigma’s, with the scale self-expressed. eg, do wOBA’s scaled so conveniently with OBP’s, distribute similarly? Or are there miles to go before we can sleep?  (Quote)

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  4. Whenever I have a decision between using an obscure stat or explaining what I mean in plain English, I try to do both. First by explaining, then using the stat to back up my theory. But I prefer English.

    I’m a tweener. I like learning about new stats but don’t let them overrule common sense. In my experience, statistical analysis has generally SUPPORTED the axions of the game I grew up with, with a few notable exceptions. My only complaint with Sabermetric types is when debating them, they have one stat that they think is the be all and end all. The game isn’t that simple, and that’s the beauty of it. Just when you think you have it nailed down, the ground shifts beneath you.

    There are things that slip through the cracks, and all the stats in the world don’t help you know how they fit together. Stats are pixels, tiny little bits of information. In order for them to have meaning, you have to step back and see the complete picture. Too many Sabermetric types fail to do so.  (Quote)

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  5. The people out there who claim that they “don’t need no stats” then turn around and tell us that Jeter will hit .335 this year, which is, of course, a stat. What many of these people are really saying is that they really don’t need any NEW stats, which is fine for them. But their antipathy towards new information doesn’t devalue the new information. It just means they have all the info they need to form their almost entirely subjective opinions, which are based far more on the emotions of a fan than on any objective analysis of a particular player, or upon the game itself. By the way, Sandy Koufax’s stats certainly DO show he belongs in the Hall of Fame. Stats do not conflict with the truth; they simply cast a light on particular aspects of the truth not always readily apparent at first glance. Bill (ondeckcircle.wordpress.com)  (Quote)

    [Reply To This Comment]

    Steve S. Reply:

    I couldn’t agree more. Many of those same people will decry Don Sutton or Andre Dawson getting into the HOF based on their aggregate stats, and then when you try to explain that rate stats are the better way to look at players, they glaze over.

    But little by little, sabermetrics is sinking in. People are starting to get the concept of judging a player against replacement level, OBP, OPS and WHIP are mainstream, and most people know BA is a lesser option to evaluate a hitter. It’s happening, just in small steps.  (Quote)

    [Reply To This Comment]

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