Throughout Fantasy Baseball for Smart People, I made an effort to detail how I try to structure daily fantasy baseball teams that will benefit from chaos—antifragile lineups that excel when “things go wrong.”
Antifragility is of course in opposition to fragility. A wine glass is fragile—it is harmed by volatility—while Skip Bayless’s income is antifragile; the more we talk about that asshole, even if it’s with complete disdain, the more he benefits.
In between those two extremes, though, is what Nassim Nicholas Taleb calls the “robust”—things that neither benefit nor are harmed by volatility. A diamond is an example of something that’s robust; unlike a wine glass, it isn’t harmed when you drop it (but it also doesn’t benefit in any way). It’s indifferent to chaos.
My goal when selecting pitchers is to be robust. I want consistency. I want predictability. I want pitchers on whom I can rely, even if the value isn’t there in terms of projected points and cost. The reason is that, due to the day-to-day consistency of pitchers, there’s not as much of an opportunity to reap rewards from being antifragile. Yes, you stand to benefit if you fade Kershaw and King Felix on a day when they’re highly owned but manage to tank—that’s certainly antifragile—but the probability of that happening is incredibly low. Whereas even the best offenses in optimal situations can still be held to a run or two, the odds are much lower that the three most expensive pitchers will all turn in duds, for example.
I want my lineup as a whole to be antifragile, at least in tournaments, but that doesn’t mean I need to be antifragile at every single spot. This is a similar concept to balancing value with usage; yes, a completely contrarian lineup stands to benefit immensely if all of the players perform well, but as you forgo greater levels of value, you’re necessarily decreasing the chances of your lineup putting you in position to actually benefit. Even if you could guarantee a large GPP victory if all of your players return value, for example, it wouldn’t be worth the struggle if the odds of that happening are 1-in-one-million. Thus, my pitcher selection is very much about “staying in the game.” I want a high enough floor from my arms to give my bats a chance to win it for me. In that way, I take a cash-game-oriented strategy toward choosing pitchers and a GPP-oriented approach toward batters, regardless of the league type; I try to be fearful on pitchers when others are greedy and greedy on hitters when others are fearful.
Start With the Arms
When you’re building a house, you can’t just start with some weird-ass overhanging room in the upper level. You need to create a foundation on which everything else can be built, and if your foundation is sloppy, the house will come crashing down and you won’t be able to play daily fantasy sports for at least a couple days, which is sad.
I think the same idea is true in a number of areas. In business, rapid growth is often proceeded by a period of risk-averse foundation-building. In terms of personal wealth, it makes sense to minimize downside (by initially saving money, getting health insurance, and so on) before becoming more risk-seeking with different types of investments. Build a robust foundation now, when it’s easy.
I take a similar approach to daily fantasy baseball lineup construction, typically starting the process with my arms. I might use three or four pitchers in a given day on DraftKings, mixing and matching different combinations, but I’d say I start with those guys in my lineup and build around them 90 percent of the time. Once that robustness is in place, it’s easier to take on risk with my bats without unnecessarily reducing the probability of a big score. And again, this difference in philosophy—when it’s smart to seek risk and when it’s not—boils down to positional consistency on a day-to-day basis.
Consistency Is King
Pitchers are clearly more consistent than batters from game to game, which is why allocating a large percentage of your salary cap to your two hurlers on DraftKings is smart; you’re increasing your lineup’s floor and upside at the same time.
Even within the pitcher position, though, there are different levels of consistency. Outside of GB/FB rate, K/9 has proven to be the most consistent stat for pitchers—far more consistent than ERA, WHIP, and even BB/9.
That means that the flamethrowers who generally rack up a lot of Ks are also the most consistent types of pitchers. They rely on a consistent stat for fantasy production, not something that’s rather volatile like earned runs or, worse, wins.
And which types of pitchers are the ones who generate a lot of strikeouts? The expensive ones, dummy. Thus, not only is it smart to pay top dollar for expensive pitchers because they’re more reliable than hitters, but also because they’re more reliable than other pitchers (not just in terms of bulk production, but rather in terms of how consistently they produce at specific rates).
Using the FanGraphs Stat Correlation Tool, I charted the correlation between various pitching stats from one year to the next (with the ‘next’ year being Year Y+1). The correlations that are in boxes are those for how well a specific stat predicts itself. How much does a pitcher’s ERA carry over from year to year, for example? The data suggests not all that much…
There’s a 0.311 strength of correlation between a pitcher’s ERA from one year to the next, which isn’t very strong. Compare that to 0.703 for K/9, for example, or 0.752 for GB/FB. Pitchers who induce a lot of ground balls or whiff a lot of batters tend to do so every year, while a pitcher’s ERA can fluctuate to a large degree.
I’m analyzing season-to-season numbers because I think they have usefulness on the nightly level. Yes, the odds of an individual hitter going deep or a single pitcher racking up 12 Ks isn’t great in any given game, but if you’re continually giving yourself exposure to the players with the highest probabilities of favorable outcomes—the players who are expected to produce over the long run—the variance will eventually even out. With daily fantasy baseball, you’re just trying to assert those small edges here and there, night in and night out.
Going back to ERA, you can see that the best predictors of it, by far, have been xFIP and (in particular) SIERA. This is the reason I emphasize SIERA when analyzing my arms: it works. When a pitcher’s ERA is up early in the year but his SIERA is low, it suggests he isn’t throwing the ball that poorly and that’s probably a great time to buy low on him. And vice versa, when the ERA is down but the SIERA is up, there’s a good chance that DraftKings has that pitcher overpriced.
Note that K/9 is actually better than past ERA at predicting future ERA. The correlation between K/9 and ERA in Year Y+1 is -0.352. The negative value doesn’t mean anything other than that as strikeouts increase, ERA decreases. So not only are strikeouts extremely consistent and a massive part of a pitcher’s fantasy value, but they also predict success in other areas—like allowing runs—better than you might think. And if you look at batting average, you’ll see that K/9 is actually the best predictor available, i.e. the most accurate way to predict a pitcher’s future batting average allowed is to look at his strikeout rate.
We see similar effects across the board with pitcher stats, with SIERA and K/9 being the shit when it comes to making accurate predictions.