MLB Hall of Fame - Lesson 01 - Advanced Pitching Stats

Jonathan Bales is the author of Fantasy Baseball for Smart People—a 197-page book created to help you win playing daily fantasy baseball on DraftKings. Baseball was the first major sport to revolutionize the way teams approach the game through the use of statistics. The “Moneyball” revolution…

By DK Playbook May 31, 2020, 9:00pm PDT

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Jonathan Bales is the author of Fantasy Baseball for Smart People—a 197-page book created to help you win playing daily fantasy baseball on DraftKings.

Baseball was the first major sport to revolutionize the way teams approach the game through the use of statistics. The “Moneyball” revolution brought with it a plethora of amazing stats that nerds like me use to help quantify and predict performance.

As baseball fans, we’re extremely lucky to have such awesome tools at our disposal. While many NFL coaches are still punting on 4^th and 1 in opponent territory and some NBA coaches still don’t know how to properly handle two-for-one situations, MLB teams almost across the board—excluding my hometown Phillies—embrace and utilize analytics.

There are also a number of incredible advanced statistical sites to leverage in daily fantasy sports, with FanGraphs at the forefront. I use sites like FanGraphs on a daily basis to analyze advanced stats. For pitchers, here are my four favorites to use.

K/9

Okay, so K/9—strikeouts per nine innings—isn’t considered an advanced stat in the conventional sense. It’s simple, but that’s what makes it so beautiful. There’s only one stat that’s more consistent than K/9 for pitchers. K/9 is extremely useful in projecting strikeouts and fantasy performance, especially on a daily fantasy site like DraftKings that rewards Ks so heavily.

Whereas many stats like ERA are better predicted with advanced stats other than themselves (past ERA doesn’t predict future ERA very well), the best predictor of strikeouts is past strikeouts. Due to its predictive ability alone, I’m listing K/9 here as an advanced pitcher stat to utilize.

Also note that, although most players understand that strikeouts are important on DraftKings, few grasp how much they improve a pitcher’s upside (and also his floor). I rarely roster a pitcher who doesn’t have above-average strikeout ability, even in cash games.

xFIP

Expected Field Independent Pitching (xFIP) is a derivation of Field Independent Pitching (FIP)—a stat that measures what a pitcher’s ERA “should be” based on what we’d expect with league-average Batting Average on Balls In Play (BABIP). It has been found that a pitcher’s BABIP is mostly due to luck—certain pitchers will be better than others at allowing balls to be hit, but once a ball is in play, whether or not it falls for a hit is influenced heavily by randomness—which means that we can use BABIP to determine how lucky or unlucky a pitcher (or batter) has been with how hits have fallen.

FIP is useful because it predicts future performance, and xFIP takes it a step further by adjusting ERA based upon home run rates. Like BABIP, the number of home runs per fly ball allowed is altered significantly by luck. When a pitcher has allowed a high percentage of fly balls to go over the fence, he’s probably been unlucky, and thus his ERA is likely to improve in the future from nothing but better luck. xFIP accounts for this luck in BABIP and HR/FB to provide a “truer” ERA.

SIERA

My favorite catch-all pitching stat is SIERA—Skill-Interactive ERA. SIERA, provided at FanGraphs, attempts to adjust ERA based on what sort of BABIP and HR/FB we should expect to see from a pitcher based on his skill level and batted ball profile. A pitcher who allows more ground balls, for example, shouldn’t be expected to give up home runs at the same rate as a fly ball pitcher.

The reason I like SIERA is because it works. Below, I charted the correlations between a variety of statistics from one year to the next. The red boxes show how well a particular statistic in Year Y predicts itself in Year Y+1

Looking at ERA, you can see that SIERA is the biggest predictor—even stronger than ERA’s ability to predict itself—followed by xFIP, and then K/9. The K/9 correlation is negative because as strikeouts increase, ERA decreases. It’s really interesting that a pitcher’s strikeout rate can predict his future ERA better than his past ERA. You can also see that SIERA is the strongest predictor of future WHIP, while K/9 best predicts batting average against.

GB/FB

Finally, one of my favorite stats that goes overlooked is GB/FB—ground balls per fly ball. For pitchers, ground balls are outstanding; they don’t leave the park, rarely turn into extra-base hits, and lead to double-plays. For the most part, the more ground balls a pitcher can force, the better.

GB/FB is important in determining a pitcher’s matchup, too. I like to study batted ball profiles to see which pitchers give up a lot of ground balls and which batters hit a lot of ground balls. When a ground ball pitcher faces a team that hits the ball on the ground a lot, that’s a really favorable situation for the pitcher. Only fly ball hitters seem to have much success off of ground ball pitchers.

Also, looking at the chart above, you can see that GB/FB is the most consistent stat we have for pitchers. With an r-value of 0.752, a pitcher’s GB/FB rate carries over really well from one year to the next, i.e. the pitchers that allow the highest rate of ground balls tend to do so on a very consistent basis; it’s even more consistent than strikeouts for pitchers.

How to Use Advanced Stats

Advanced stats should be utilized to make better predictions. Whether that stat is simple (like K/9) or relatively complex (like SIERA) doesn’t really matter; if it can help us better identify player value, then it’s useful.

Of course, just because a player excels in a particular area doesn’t mean he’s going to offer value on DraftKings. Clayton Kershaw’s advanced stats are insane, but if he’s priced ridiculously high, he might be a poor value. It all depends on how anticipated production matches the price tag.

Thus, it’s always important to get an idea of which factors are a component of DraftKings salaries and which aren’t. For the most part, players are going to be priced according to public opinion, and the public cares more about simple stats like ERA and wins than they should.

That means that what really matters is how a particular advanced stat compares to a pitcher’s more commonly viewed numbers. If a pitcher starts the year 2-4 with a poor ERA but has much better SIERA and K/9 numbers than we’d expect for someone with his ERA, it’s a sign that 1) he’ll improve in the future and 2) he’s probably underpriced in daily fantasy baseball.

Compare that to a very similar pitcher who begins the year 2-4 with a poor ERA, but has poor SIERA and K/9 numbers to accompany it. That player might cost the same amount on DraftKings, but the stats suggest he’s throwing really poorly, and perhaps still overpriced.

The key to using advanced stats, then, is understanding how they fit into the bigger picture and using discrepancies between advanced stats and basic stats to identify value on DraftKings.