The Playbook, Inning 6: Nine must-follow fantasy baseball tips
By now, you might be fancying yourself a fantasy baseball pro.
Inning 1: Fantasy baseball 101
Inning 2: League formats
Inning 3: Salary-cap drafts
Inning 4: Preparation
Inning 5: Roster optimization
Inning 6: Nine must-follow tips
Inning 7: Adjust to league trends
Inning 8: Utilize advanced stats
Inning 9: Master the player pool
You’ve read all five Playbook innings to date, and perhaps have even begun to craft your own cheat sheet for when the 2022 season ultimately begins. You’re feeling confident in yourself, fully trained for the proverbial marathon that’s ahead. But while the force is with you, young Skywalker, a Jedi yet you are not.
It’s not enough to simply know the basics of this grand game. No, we won’t stop until we’ve made a perennial championship contender of you. After all, it might be fun to play fantasy sports, but isn’t winning ultimately the most fun?
So let’s take these important next steps with nine strategies for you to embrace — angles that will make you a more competitive player. While they’re strategies that any experienced player might already know, they’re also topics with which anyone could use a refresher course.
Rotisserie baseball was spawned from the bubble gum card era, a time when television graphics included just “AVG-HR-RBI” for hitters and “W-L-ERA” for pitchers, and in a season when it was still possible for Steve Stone to win a Cy Young award, despite an ERA seven-tenths of a run higher than and a WAR (Wins Above Replacement) between 2-3 less than that of Mike Norris (depending upon your source). Baseball analytics have come a long way since then and, while the majority of us are more educated players today, the game hasn’t necessarily kept up quite as well with the times.
That’s not to say that wins, batting average and ERA have no place in fantasy baseball. Consider them to be a form of accounting for past outcomes, which isn’t an entirely unfair measure of success for our purposes, but rather one that accepts that baseball is, in itself, a game of occasionally unlucky bounces.
From a future-analysis standpoint, however, the value of these categories stands at zero (or very close to it). The following examples exemplify the folly of chasing wins, batting average or ERA:
Wins: Jacob deGrom‘s 2.08 ERA over the last three seasons combined was the majors’ best among qualifiers (and by a three-quarters-of-a-run margin), yet he won only 22 times in 59 starts. By comparison, Julio Urias won nearly as often — 20 times — in 2021 alone, despite an ERA nearly nine-tenths of a run higher (2.96) than deGrom’s three-year number.
Batting average: Nicky Lopez’s .300 batting average last season placed him 14th among qualifiers, but it was backed by a .347 BABIP, 20 points higher than he had posted in any of his previous five professional seasons (minor league statistics included), 43 points higher than in those previous five years combined and 78 points higher than in his first two big-league seasons combined. Meanwhile, Max Kepler‘s .211 batting average was fourth-worst among hitters with at least 450 plate appearances, but it was obviously negatively influenced by a second-worst .225 BABIP.
ERA: Wade Miley had a 3.37 ERA last season despite a sixth-lowest-among-qualifiers 18.1% strikeout rate. To contrast, Aaron Nola had an ERA a run and a quarter higher — his was 4.63 — yet no one considers, nor should consider, Miley to be remotely close to Nola’s equal in terms of pitching talent.
Instead of weighing wins or ERA, use FIP (Fielding Independent Pitching Score), or SIERA (Skill-Interactive ERA) or Statcast’s xERA. Simpler yet, trust the pitcher’s WHIP over his ERA, or weigh his strikeout-to-walk ratio more heavily. Nola, to return to his example, had the majors’ largest qualified ERA/xERA differential in 2021 (4.63 ERA, 3.35 xERA, for a 1.28 run difference).
For hitters, consider a player’s contact rate, line-drive rate or Statcast hard-contact rate rather than to put stock in his batting average, at least if your league includes that category. From a hitting-skills evaluation standpoint, wOBA and Statcast metrics like launch angle and exit velocity are better measures. (Worry not, we’ll dive deeper into those Statcast metrics in an upcoming inning of Playbook.) Returning to the Lopez example, while his speed helps fuel a better batting average than a typical hitter’s might, he possesses some of the weakest quality-contact metrics in the league, his Statcast hard-hit metric is in the 4th percentile (26.9%), shrinking his margin for error on batted balls considerably.
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Trading was covered a bit in the last Playbook installment, but this is a specific, critical angle to understand and exploit. Just as in the stock market, the (perceived) value of baseball players on the trade market vary depending upon things like their recent performance, health, role and potentially even the success of the team around them. To “buy low” means to attempt to trade for a player at a low — and preferably the lowest — point on his valuation curve, while to “sell high” means to trade away a player at his highest point, when the interest in acquiring his services has reached its peak.
Usually, the way to identify a “buy low” or “sell high” player is to seek those who have underperformed or vastly exceeded expectations, either for the season as a whole or in recent weeks. Some of the statistics cited above can help with this: comparing FIP (or SIERA) to ERA, comparing Statcast’s xERA to ERA, comparing Statcast’s hard-contact rate to home runs or comparing line-drive rate to batting average, just to name four. Essentially, you’re engaging in similar analysis to what you should do during draft-prep season, except using in-season data to extract hidden value (or identify overvalued players). You could even compare the current year’s numbers to last year — or the past three years — if you wish, though I’d recommend still examining skills-driven departments with that.
Let’s look at some examples from 2021. At the conclusion of his 10th start of the season on May 23, Luis Castillo had one win, a 7.61 ERA and a 1.80 WHIP, after having been drafted 36th overall and 12th among starting pitchers (on average) in the preseason. That his strikeout rate had plummeted, to 19.9%, not to mention the season had extended deep enough to cast full-season concerns about his rebound prospects, surely caused his trade stock to slip in the mind of many of his managers. Still, Castillo’s 4.80 FIP during that same time span, not to mention his absurd .389 BABIP, indicated that he was ridiculously unlucky during that near-two-month time span, and certain to improve to some degree. Sure enough, he would swiftly turn the corner from there, posting a 2.76 ERA and a 25.5% strikeout rate over his final 23 starts, allowing as many as four runs in only three of them, while performing as a top-25 fantasy starting pitcher. He was as superb a Memorial Day-range “buy low” as anyone.
From a “sell high” perspective, while he didn’t garner nearly the draft-day attention as Castillo, yet finished one spot outside the ESPN standard’s top 250 draft spots using ADP (251st overall), Matthew Boyd got off to the kind of April start that makes a player an instant “shop him” type. He went 4-of-6 in quality starts with a 2.27 ERA, giving him the façade of his 2019 first-half, standout self. Boyd’s 3.03 FIP and meager 17.3% strikeout rate, however, indicated that much of the performance was a mirage, meaning that his managers should’ve cashed in his chip for whatever they could. Boyd’s two IL stints from that point forward might have been difficult for anyone to forecast, but between those he managed only a 5.23 ERA and one win in nine starts over the season’s final five months.
Usually, fantasy managers who attempt the “buy low, sell high” strategy misstep. They often attempt such a deal too early in the season, before their competitors’ opinions of players begin to significantly shift, or they’re too unrealistic in gauging the market for such candidates. Such miscalculations can turn off a prospective trade partner, often to the point that there’s no future hope of successfully executing the strategy.
The idea here wouldn’t have been to try to sneak Castillo away from his manager for a borderline roster-worthy player in an ESPN standard 10-team league (which would be roughly the value of an outside-the-top-25 third baseman) or to expect a top-50-overall-valued player in exchange straight up for Boyd. No, the idea would have been to acquire Castillo for anything noticeably cheaper than the 25th-most-highly-regarded-on-that-date starting pitcher, or to trade Boyd away for anything noticeably better than a late-round ESPN standard pick, meaning anything definitively roster-worthy.
“Streaming,” or rostering a player for one day (or week, depending upon your league’s lineup-locking format), only to release him the next for that day’s similar replacement, is an increasingly popular strategy in fantasy baseball, especially shallow mixed leagues and those that afford you the maximum opportunities to change a lineup. The idea is that in a league that weighs cumulative statistics — such as a points-based league where every player’s performance is boiled down to a single number, or a rotisserie league light on ratio categories like batting average, ERA or WHIP — you want to maximize your number of player opportunities to accumulate such stats. This means trying to get an active game out of every single one of your active lineup spots, every day, and in ESPN standard leagues, you get the benefit of changing your lineups each and every day.
Nowhere does streaming benefit a fantasy manager more than on the pitching side. Pitching statistics tend to be much more volatile than hitting statistics, and starting pitchers in particular work significantly less often than hitters — generally once every five days, so keeping the same starting pitcher in your lineup for an extended period means getting generally one start (and maybe two) from him each week. Streaming starters in a daily league provides you the opportunity to try to squeeze a start out of every pitching lineup spot every day, maximizing your chances at getting fantasy points or, in a roto league, wins and strikeouts. (In the latter, however, bear in mind that this strategy can come at expense to your ERA and WHIP, since most pitchers readily available on a league’s free-agent list are less talented than those already rostered.)
Again, the format of your league comes into play here, as does whether or not your league limits the number of transactions or starts you’re allowed in a given week, but the closer your league to fully points-based, daily transactions and no limits on either moves or starts, the more the strategy of streaming starters benefits you. After all, only 24% of all starts last season resulted in a negative point total in ESPN standard points leagues, giving you good odds of a strong return on the strategy (albeit with a hint of risk).
In a weekly league, incidentally, streaming starters is every bit as valid a strategy, only there it’s often referred to as loading up on “two-start” pitchers in a given week, picking those set to start early enough in the week that they’d be able to squeeze in a second turn before Sunday’s games conclude.
As an additional piece of advice regarding ESPN standard leagues: Blow past the weekly starts cap, if your league has one. This means that if your league limits you to 14 starts in a given week (an average of two per day), then on the day that you expect to reach your maximum for that week, you should stream everywhere you can. Our cap rules only take effect at the beginning of a new day, but don’t lock you out on the day you reach or exceed said cap, meaning that a clever manager could enter a Sunday with 13 starts already in the tank, then stream six starters on Sunday for a total of 19. (Incidentally, one reason to argue this be allowed is that, in the event of a team exceeding the cap, it would be impossible to tell which pitcher was responsible for the final start under said cap — would it be the one whose game started first, whose game became an official game first, or the one whose game finished first?)
Tying to the previous point about streaming, you want to try to squeeze as many opportunities to generate statistics out of your players as possible. Besides manipulating fantasy lineups, there are other ways to do this. Drafting or acquiring hitters from more productive offenses, hitters who hit earlier in the lineup, hitters whose teams have more favorable daily or weekly matchups or pitchers who can claim the same on that side. Returning to the previous topic about wins, too, in those leagues you can also accumulate pitchers who work for the most successful teams.
Seeking players from productive offenses is self-explanatory. The more runs a team scores, the more runs and RBI it will spread up and down the lineup. For example, of the 20 hitters to drive in at least 100 runs last season, 13 played (including, at least in part, in Adam Duvall’s case) for teams that ranked among the top 10 in terms of runs per game, and seven of those 13 played for top-five offenses. On the pitching side, of the 13 pitchers to win at least 14 games last season, eight pitched for teams that ranked among the top eight in terms of runs per game on offense.
It’s the lineup advantage that’s oft-overlooked in fantasy, but it’s a relevant one. Coupling this somewhat with the previous point, the more times teams score, the more times they cycle through their lineup. Therefore, the higher a hitter bats in the lineup, the more opportunities he’ll get to hit in a given game, and over the course of a season, that can amount to some noticeable volume advantages. The chart below breaks down the average number of plate appearances by each of the nine lineup spots for the 2021 season, with the totals by the majors’ best and worst from each spot.
First off, the league as a whole saw a 2.6% reduction in total plate appearances in 2021, compared to the most recent full season before it in 2019. Interestingly, that affected the bottom four lineup spots (2.7% decline) more than it did the top two (2.3% decline), further strengthening the volume-chasing case for top-of-the-order hitters.
While neither the 2.6% league-wide reduction in total plate appearances, nor the 18-plate-appearance difference between average teams’ Nos. 1-2 hitters might seem like much over the course of a 162-game schedule, it nevertheless represents an opportunity advantage. The 86-PA difference between the Nos. 2 and 7 hitters, meanwhile, is massive. That’s why hitters slated for “bottom-third in the order” roles are at a significant disadvantage, and that’s increasingly true when the competitive levels of the offenses are unequal — see the 137-PA difference between the best team’s No. 2 and worst team’s No. 7 hitter.
Daily or weekly matchups themselves also influence opportunities. Hitters set for a week of games at nothing but hitter-friendly ballparks are likely to see their teams score more runs, meaning more trips to the plate for the offense as a whole and more runs/RBI up and down the lineup. These are every bit as important to weigh — if not more so — in your lineup-setting as the players’ roles themselves.
I get the lure of these silly numbers. Assuming that it starts on time, spring training baseball represents the first moments of competitive, recordable game action in four months, and as stats-obsessed baseball fans, we crave new statistics. By March 1, we’re ready to dive right into these new numbers, often to the point we get carried away with players’ spring performances and make unnecessary, and almost always unadvisable, adjustments to our cheat sheets.
Here are the problems with spring statistics: They’re drawn off a minuscule, roughly one month or 30-day sample, and one that, unlike during the regular season, features prominent players playing only fractions of the games themselves or often not many of them at all (especially in the early weeks). They’re also played in states where weather conditions are quite different from what the same teams will see during the regular season, as Cactus League games in Arizona are played at 1,000-plus-foot elevations, often in humidity, pumping up the offensive numbers, while Grapefruit League games in Florida are played at or near sea level, in often larger ballparks that favor pitchers. And, perhaps most importantly, they’re played against far more variable levels of competition than what we’d see during the regular season, as expanded rosters mean that certain players could capitalize from facing nothing but inexperienced, Class A ball competition for a good number of their at-bats or innings.
Remember when Jung Ho Kang led the majors with seven spring homers? You should, considering it happened in 2019.
Nowhere is the absurdity of spring statistics more apparent than in the saves category. In the past three full spring trainings (2018, 2019 and 2021), 11 pitchers had a three-save spring: Jonathan Aro, Ryan Brasier, Cody Carroll, Dietrich Enns, Justin Hancock, Eric Hanhold, Andrew Kittredge, Dominic Leone, Lucas Long, James Teague and Hunter Wood. These pitchers went on to save a grand total of zero big-league games during the regular seasons that followed. The reason is that big-league teams tend to lift their veteran players from spring contests early, usually by the sixth inning, meaning that it’s those same Class A-caliber players who are often left to pitch the eighth and ninth, not to mention that teams prefer to get their real closers work against real big-league hitters earlier in the game if they can. You’d expect to see a Raisel Iglesias pitch the fifth, not the ninth, in the spring.
If there’s a spring-stats angle worth exploiting, it’s those unproven types who have something to prove or a job to claim. Robbie Ray‘s 1.98-ERA, 34.6%-K rate spring 2021 is a spectacular example of this, not because the raw stats themselves said something, but rather that they illustrated returns on the offseason conditioning and increased focus he brought into training camp. Another statistical factor to consider is whether a player’s strikeout or walk rate has noticeably shifted from previous seasons, such as when Dylan Cease struck out 22 batters in 17 spring innings, perhaps hinting at what was to come in 2022.
For a final note on those spring stats, if you’re insistent in placing any stock in them at all, a wise move is to peruse Baseball Reference’s “strength of competition” number, which in recent seasons the site has provided as an additional column beside their spring statistics. If a player’s level of competition faced falls in a Class A-level tier described by their metric, his stat line is much less relevant than one who faced a great deal of Triple-A or MLB talent.
Speaking of those saves, while I’ll stop considerably short of the blanket “don’t pay for saves” declaration, there’s still a lot of merit to the strategy. Saves are typically the easiest of the 10 traditional roto statistics to find readily available on the free-agent list, or at worst, at a discount price on the trade market.
To that point, 45% of the majors’ total saves last season came from pitchers who were unquestionably not drafted in ESPN leagues (specifically outside the top 450 ADP), including standout Emmanuel Clase and fellow 20-save performers Ian Kennedy and Lou Trivino. Another 5% of the league’s saves came from pitchers whose ADPs were between 301-450, meaning that half of the majors’ total saves recorded came from pitchers who would’ve cost a song in a shallow mixed league.
Again, though, I hesitate to use the word “DON’T” when it comes to investing in saves, because a lackadaisical approach to the category is another type of mistake. The deeper the player pool your league uses — think AL- and NL-only — the more likely it will be that managers will roster players who might even sniff a save chance, meaning that the free-agent list won’t be nearly as populated with prospective save-getters. Worse yet, trade partners are much less likely to want to trade a pitcher once he’s handed his team’s closer role, especially in a season like 2021 in which more and more teams shifted towards committee closer strategies.
Fantasy managers on the whole, and not just baseball but in all sports, tend to find chasing yesterday’s statistics irresistible. A hitter slugs three home runs on a given night, and he becomes the hottest commodity in the game by the next morning. The same goes for the pitcher who just threw a no-hitter. But even for the more experienced players, who aren’t fooled by a one-night outburst, some do get fooled by lengthier stretches, albeit still over still-small samples of time, of player success. If you see the phrase “small sample size” bandied about on these pages, this is what we’re cautioning against.
Recency bias can reveal itself with the one-year wonder, such as the aforementioned Miley but also in the contrasting case of DJ LeMahieu, who had a miserable year that was probably adversely impacted by injuries that eventually led to core-muscle surgery after the season. In LeMahieu’s case, it’s important to account for the effect of that on his performance, while not forgetting the rather-productive years that came before it.
Another area where the recency bias traps even the best of us is during the regular season’s early stages, where again the freshness of new statistics lures us in and causes us to believe outcomes that haven’t yet fully crystallized. At the three-week point of the 2021 season, fantasy managers who fell for early small samples surely fully believed in Yermin Mercedes’ breakout, as he was batting .407 with four home runs and 12 RBI through 16 games or Danny Duffy’s rebound being evidenced by three straight quality starts and an 0.50 ERA or that Lucas Giolito was doomed to disappoint after his Patriots Day disaster start (1 IP, 8 H, 8 R, 7 ER).
Be patient, especially early in the year, because baseball tends to even out the larger the period of time you’re examining.
Who doesn’t want to be the first person to discover the next big thing? The lure of rookies has taken on greater weight in recent seasons, with such standouts as Aaron Judge and Pete Alonso, both of whom set single-season rookie records for home runs (2017 and then 2019), Ronald Acuna Jr., Cody Bellinger, Kris Bryant, Trevor Story and Fernando Tatis Jr., and that’s just to name a small handful of the many who have excelled just in the past half-decade.
Inning 1: Fantasy baseball 101
Inning 2: League formats
Inning 3: Salary-cap drafts
Inning 4: Preparation
Inning 5: Roster optimization
Inning 6: Nine must-follow tips
Inning 7: Adjust to league trends
Inning 8: Utilize advanced stats
Inning 9: Master the player pool
The problem with rookie-chasing, though, is that for every Judge or Acuna, there’s a Jarred Kelenic, Sixto Sanchez or Bobby Witt Jr., rookies who either got hurt, disappointed or didn’t even get the call at all in the season in question. Yes, rookies and younger players have had greater odds of success in recent years than at any other time so far this century, but it’s still important not to overrate each season’s freshman class, especially not at the expense of ignoring a more seasoned, yet still-young big leaguer who has yet to reach his peak at the big-league level.
Kelenic, in fact, serves a great description of a “post-hype sleeper,” or a player who still possesses similar talent to the scouting reports at the time of his debut, but who has thus far required more time to emerge in a prominent role and adapt to big-league pitching. He’s still 22 years old, well in advance of his prime (although that can begin as early as age 23 and span as far as age 29) and with plenty of career ahead of him with which to improve. Remember, one of the goals in fantasy baseball is to unearth value where your competition least expects it. In Kelenic’s case, his price tag is going to be lower now than where it was a year ago at this time, despite his encouraging September finish to 2021, but now everyone will have moved on to “the next big thing” — players like Witt and Adley Rutschman. Sure enough, in early NFBC drafts, Witt’s ADP was a full three rounds sooner than Kelenic’s.
That’s not to say that Kelenic is a clearly superior pick to Witt for 2022, but he surely has the clearer immediate path to playing time, especially as the lockout delays and cuts into the length of spring training, costing Witt valuable development and positional competition time. If Kelenic is truly lingering three or more rounds beyond Witt in your draft, it makes a lot more sense to wait and select Kelenic. After all, we have Kelenic projected for 553 plate appearances to Witt’s 344, not to mention that the Seattle Mariners sophomore is forecasted for 46 more fantasy points in 2022.
To repeat, baseball on the whole is an unpredictable game, full of ups and downs that only even themselves out over a full 162-game schedule. Narrowing the scope, however, there is a subset of baseball players who are even more subject to peaks and valleys than others, and it’s with these which you must be the most patient.
On the hitting side, big sluggers who hit a lot of home runs at the expense of many strikeouts, often referred to as “three true outcomes” players because of the high likelihood that the outcomes of their plate appearances will be either a home run, strikeout or walk, represent the streakiest around. The most notorious king of “three true outcomes” is Joey Gallo, who through the first seven seasons of his big-league career has seen 58.5% of his plate appearances end in a home run, strikeout or walk, and in 2021 led all of baseball with a similar 58.8% of his PAs resulting in one of those outcomes. Sure enough, during one three-week span in 2021, Gallo batted an absurd .339 (19-for-56) with 13 home runs, carrying many of his fantasy managers in head-to-head leagues, only to be traded to the New York Yankees three weeks later, where he’d hit only .140 (7-for-50) with five extra-base hits and 23 strikeouts in his first 14 games. Considering the newfound buzz resulting from Gallo’s donning of pinstripes, he surely sank quite a few teams in their matchups following the trade.
While one could attempt to use a player like Gallo as a buy-low or sell-high candidate based upon where he’s at in the performance curve, it’s a poor idea to attempt to acquire him at his high points or sour on him at his lowest. Such players are best utilized over lengthier time frames, where their fluctuations have more time with which to even out, as it’s difficult to tell when their next hot or cold streaks are coming.
On the pitching side, truly “streaky” types tend to be those who have some sort of incomplete ingredient in their games. It could be the lack of blazing, raw stuff, perhaps shaky control, or maybe a durability question. Recent-years Dallas Keuchel is a prime example. Coming off a solid-yet-unspectacular 2019, he enjoyed a productive, top-20-fantasy-starter 2020, during which he had a season-concluding, six-game stretch in which his ERA was 1.06. Keuchel then had a 10-start string of similar success early in 2021, his ERA sitting at 3.17 with five wins and six quality starts. Perhaps in large part due to a second-lowest-among-qualifiers 14.0% strikeout rate in 2020-21 combined, however, he managed an 5.74 ERA, 1.57 WHIP and 8.1% K rate in his other 27 appearances (25 starts, two relief outings) across those two seasons.
In Keuchel’s example, while patience remains a worthy strategy, remember that the greater degree of volatility on the pitching side of the ball — especially for a low-strikeout arm like him — does support a strategy of greater turnover. The takeaway is not to completely distrust the streaky pitcher, but to be more prepared to either move on when opportunities present themselves, or to make a greater effort to find replacements to fill in the gaps during their cold spells.
Always consider the nature of the player and what his skills tell you. Returning to the example of Giolito and his awful Patriots Day start in Boston, bear in mind he managed a 3.09 ERA with a 1.04 WHIP and 151 strikeouts in his final 23 starts following that game, with skills that actually appeared to be improved upon his prior years. Patience is warranted with such fluky performances!
Now you’ve got the skills necessary to be a competitive, well-educated fantasy baseball manager, so it’s time to shift our focus to prepare you for the upcoming season. In the next edition of the Playbook, we will examine the shifting trends in today’s baseball game. Stay tuned!