Royal Mythology

Rarely has the performance of a single team led to so many attempts to rationalize, explain, project virtue, and the like as the 2014-15 Royals. Focusing on the 2015 edition, here are just a handful of Royals myths that I have been particularly annoyed at hearing. The "analysis" that follows is not comprehensive nor is it intended to be. That's kind of the point. The level of extraordinary claims that have been made about the Royals should be apparent even with the crudest of inquiries into the objective record.

Myth #1: Whatever the Heck Andy McCullough Tweeted

"The entire point of the Royals is that baseball is a hard game and if you make your opponent do things, sometimes they will screw up"

The Kansas City Royals reached based on error 58 times in 2015. The AL average was 57. In 2014 they had 51 ROE versus a league average of 57.

Myth #2: The Royals Don't Make Mistakes

Errors leave a lot to be desired as a metric, but when traditional thinkers talk about making mistakes, errors are first and foremost on their mind. The 2015 Royals had a mFA of .973; the AL average was .971. The 2014 Royals had a mFA of .968; the AL average was .970.

Myth #3: The Royals had a long World Series drought

There are 30 MLB teams. It should be obvious, then, that 30 years is the expected time between world titles. Thus a streak of thirty years is not particularly long in theory. It's also not long in practice, as it was only the 12th longest drought (the Mets had the 13th longest drought). Last year en route to the pennant, two of the three teams Kansas City beat had (slightly) longer droughts and the other had a slightly shorter drought.

To find the Royals worthy of any particular sympathy, one must give extra credit for how poorly the franchise performed for much of that period. While this is unfortunate for the fans, it seems like such a group would be less traumatized by losing the World Series and more appreciative just to get there. Fan "suffering" is very low on my list of factors in deciding which teams to pull for in the playoffs, but to the extent I consider it, I tend to side with teams that have been good and just have not had the bounces go their way in October. Teams like the Marlins and the Royals who parlay their only two playoff teams in an extended period into pennants and world titles are quite galling to anyone who has rooted for a titleless yet competent franchise.

But more broadly, I think that the media and fans have yet to understand how championships will be distributed over the long haul in leagues that are double or close to it in size from what they were for so many years. Lengthy droughts, the types that the Red Sox, Cubs, or to a lesser extent Indians and Giants have suffered will be quite commonplace. Basic logic tells you that they have to be.

I did a "simulation" (which is a pretentious way of saying I used the RAND() function in Excel) to simulate 1,000 seasons of a thirty-team league in which each team had a 1/30 chance to win the World Series in any given year. Remember, this is the height of competitive balance. The probability of a championship could not be any more evenly distributed. There are no market disadvantages, no bad franchise stewardship, no billy goats. It is theoretically possible that the timing of championships could be more evenly distributed, but admittedly my imagination is insufficient to describe a specific scenario that would force a more even temporal distribution.

After 1,000 years, the average team should have had 33 1/3 titles. The most successful had 45; the two least successful each had 22 (as an aside, and granting that it was a sixteen team universe for an extended period, think about the Yankees' 27 in this context).

For years 501-1000, I calculated the average of the quartiles, as well as the percentage of active droughts as of a given year greater than 30 years. Since droughts for these 500 years are not independent of one another, be cautious with extrapolating those averages to anything else (for what it's worth, the medians are similar).

The average for these seasons was a first quartile drought of 8.4 years; a median drought of 20.2 years; a third quartile drought of 39.8 years, and a maximum drought of 115.0 years. In the average season, 34.4% of droughts exceeded 30 years (note that the current MLB figure is 12/26 = 46.2% of droughts exceeding 30 years, excluding the four subsequent expansion franchises, which suggests but in no way proves that, not surprisingly, the observed title distribution is not as egalitarian as the theoretical one used here).

Freezing it at year 1,000, this is what the drought picture looks like:


Even with new champions in 7 consecutive and 16 out of 20 seasons, a pretty typical 1/3 of droughts exceed 30 years, one team has exceeded the Cubs, and two more have exceeded the Indians.

The longest drought for any team during the millennium was 215 years. The poor fans of Team 6 celebrated a title in year 306, then went through many generations (or not, who knows, it's the future) before finally winning again in year 622. Then they waited another 120 years for good measure. Should baseball survive for 1,000 years with 30 or more teams, think about all of the narratives that the sportswriters of the future will get to craft.

Myth #4: The Royals Need to Be Explained

This is more of a meta-analytical comment than specific to the Royals, but there is an underlying notion, seen even on some sabermetrically-inclined outlets, that the Royals are an anomaly that demands our attention and an explanation. Please note that I am not criticizing the act of questioning ones premises, of attempting to update hypotheses as new data becomes available, of recognizing that we don't know everything about baseball, or anything of the sort. This all laudable. But such inquisition must not be confused with an imperative to find fault in one's null hypotheses either.

But there all too often is a reflexive desire to be too conciliatory, too eager to throw out one's existing knowledge and toolkit in an attempt to explain something that may just be a fluke. Witness "The Year That Base Runs Failed" (an article that demands a thorough undressing that I just do not have the will to give justice to right now). Recently this has seemed to manifest itself more at outlets that rely on 1) boisterous, opinionated writers and 2) daily content production.

When you are boisterous and opinionated, you need your opinions to be right in order to maintain credibility. If you have to blame the tools (Base Runs, W% Estimators, the entirety of sabermetric theory) that you used to justify your initial opinion, that's fair game. On the other hand, my position on the Royals doesn't demand I apologize for it (maybe I should--as I acknowledged above, I could be wrong, and inquiry into why that might be the case is healthy). My position is simply that the Royals were a fairly average team as indicated by their component statistics, but that sometimes teams outplay their component statistics. The Royals made the playoffs and over two seasons went 22-9, but a .500 team would go 22-9 or better with 1.5% probability--it's not likely but it also must happen now and again. You can disagree, but it's inherently a passive argument.

If you need to produce content daily, then you have to write about something, and writing "the sample size precludes us from drawing firm conclusions" over and over again doesn't drive readership. So there's a temptation to overfit your model, to declare that the secret sauce has been found, to cheat on the degree of certainty you require before you declare correlation to be causation, to investigate one positively correlated variable at the expense of other potential explanatory variables, to overreact to a year in which your metric's standard error is higher than it typically is.

Even great sabermetricians can get caught in this trap, and I have never been confused with a great sabermetrician but I have written things along these lines that I am not proud of as well. Bill James and Nate Silver have both, using different but understandable means when considered in the context of their work, failed pretty miserably at predicting playoff success based on historical data. The simple fact of the matter is that there were 32 playoff games (not counting the wildcard games) this season, which is fairly typical. At 30 games/season, you need five seasons to have a sample size the same as that of one major league team-season.

This is particularly problematic when so many of the attempts to explain playoff performance are based on theories about changes in the game. Contact superseding Moneyball, bullpen construction and usage patterns which have been in a constant state of change throughout baseball history...you could never have credible data without the conditions of the game shifting. This is not to say don't try to advance our understanding, it's to say be extremely cautious as you attempt to do so.

So what winds up happening is that a potential explanation ("Contact works, allow it" is a particularly poor paraphrase since it makes it sound like your pitchers should allow contact, but I saw that Colin Cowherd promo to many times not to use it) is honed in on, and maybe there's evidence of some effect, so other potential explanatory variables are ignored and the correlation is exaggerated and soon there's a truism that must be disproved rather than a hypothesis which must be proved.

There's a difference between saying "I don't know" and "No one will ever know". If it seems as if my school of thought arrives at the latter, that's a fair criticism. But I personally would rather be too certain about how much I can't know than to be too quick to think I've learned something new.