By now, you might be fancying yourself a fantasy baseball pro.
You’ve read all five Playbook editions to date, and perhaps have even begun to craft your own cheat sheet for when the 2020 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, but you are not a Jedi yet.
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. Here are nine strategies you need familiarize yourself with, 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.
1. Wins, batting average and ERA are poor barometers of talent
Rotisserie baseball was spawned from the bubble gum card era, a time when television graphics included “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 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, 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 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, these categories’ value stands at zero (or very close to it). These exemplify the folly of chasing wins, batting average or ERA:
Jacob deGrom’s 2.01 ERA during the past two seasons combined was the majors’ best among qualifiers — by a half-run margin at that — yet he won only 21 times in 64 starts. By comparison, Rick Porcello won 22 times in 33 starts in 2016 despite an ERA more than a full run higher (3.15), not to mention Porcello won 31 — 10 more than deGrom — of his 65 starts in 2018-19 combined despite a 4.87 ERA — that’s more than 2 ¾ runs higher than deGrom’s. Tim Anderson’s .399 BABIP, or batting average on balls in play (this excludes at-bats that result in a home run or strikeout), in 2019 was the second-highest by any hitter who qualified for the batting title in any of the past 17 seasons, fueling a major league-leading .335 batting average. Meanwhile, Marcell Ozuna’s .241 batting average was 15th-worst among 135 batting title-eligibles in 2019, adversely influenced by a .257 BABIP that ranked 10th-worst. Dakota Hudson last season became the first pitcher in more than 15 seasons to post a sub-3.40 ERA in a year in which he struck out fewer than 20% of the batters he faced while walking more than 10% of hitters; his ERA was 3.35. To contrast, World Series MVP Stephen Strasburg had a near-identical ERA — his was 3.32 — yet no one considers Hudson close to Strasburg’s equal in terms of pitching talent.
Instead of weighting 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 weight his strikeout-to-walk ratio more heavily.
For hitters, consider a player’s contact rate, line-drive rate or Statcast hard-contact rate rather than 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 Playbook.)
2. Buy low and sell high on the trade market
Trading was the subject of the last Playbook installment, but this is a specific, critical angle to understand and exploit. Just as in the stock market, baseball players’ (perceived) values 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.
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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 you’d do during draft-prep season, except using in-season data to extract hidden value (or overvalued players). You could even compare the current year’s numbers to last year’s — or the past three years’ — if you wish, though I’d recommend still examining skills-driven departments with that.
To extract successful such examples from 2019, on May 22, Eduardo Rodriguez had a 5.43 ERA and 1.46 WHIP in 10 starts, after having been drafted 38th among starting pitchers on average in the preseason, but he also had 61 strikeouts and a sixth-worst-in-baseball .355 BABIP that suggested unusually poor fortune on balls in play. He would win 15 of his next 24 starts behind a 3.21 ERA, rating as one of the 20 best starting pitchers in fantasy during that time span and a superb May “buy low.”
From a “sell high” perspective, at the conclusion of play on June 25, Ian Desmond’s seasonal line was that of .280/.340/.526 slash rates, 11 home runs and 41 RBIs through 79 Colorado Rockies games, but perhaps more importantly, he had batted .354 with eight of those homers in the seven-week period ending on that date. As Desmond was the No. 137 player selected overall on average in the preseason, that was the prime time to trade him, considering he had begun to lose his grip on an everyday role — he had only 56 starts in those 79 Rockies games — had been as free-swinging as ever and was riding a bloated .458 BABIP during that seven-week hot spell. Desmond would start only 50 of the Rockies’ final 83 games, batting .227 with nine homers.
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 Rodriguez away from his manager for a borderline roster-worthy player in an ESPN standard 10-team league — that’d be roughly the value of the No. 70 overall starting pitcher — or to expect a top-50-overall-valued player in exchange straight up for Desmond. No, the idea would have been to acquire Rodriguez for anything noticeably cheaper than the 38th-most-highly-regarded-on-that-date starting pitcher, or to trade Desmond away for anything close to his original No. 137 ADP, considering there was already some erosion to his value.
3. Stream starting pitchers
“Streaming,” or rostering a player on 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 weights 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 specifically 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 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 streaming starters benefits you. After all, only 25% 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 affords you 14 starts in a given week, or 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’d 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?)
4. Volume is king, especially in a points league
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 RBIs it will spread up and down the lineup. For example, of the 22 players to drive in at least 100 runs last season, 14 played for teams that ranked among the top 10 in terms of runs per game, and nine of those 14 played for top-five offenses. Similarly on the pitching side, all seven of the pitchers who won at least 17 games pitched for teams that ranked top-seven 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 2019 season, with the totals by the majors’ best and worst from each spot.
| Lineup Spot | Worst Team | Average Team | Best Team |
|---|---|---|---|
| 1 | 734 | 761.1 | 786 |
| 2 | 723 | 743.0 | 772 |
| 3 | 703 | 725.6 | 756 |
| 4 | 685 | 709.0 | 744 |
| 5 | 671 | 693.4 | 727 |
| 6 | 651 | 675.3 | 703 |
| 7 | 629 | 657.2 | 681 |
| 8 | 611 | 637.7 | 663 |
| 9 | 592 | 617.6 | 645 |
While the 18-plate-appearance difference between average teams’ Nos. 1-2 hitters might not seem like much over the course of a 162-game schedule, it nevertheless represents an opportunity advantage. The 86-PA difference between 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 143-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 hitting-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.
5. Spring training stats don’t really matter
I get the lure of these silly numbers. Spring training baseball represents the first time with 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 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 was just last season.
Nowhere is the absurdity of spring statistics more apparent than in the saves category. In the past three spring trainings, four pitchers had a four-save spring: Stefan Crichton, Dietrich Enns, Dominic Leone and Corey Taylor. 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 Kenley Jansen pitch the fifth, not the ninth, in the spring.
If there’s a spring-stats angle worth exploiting, it’s this: Unproven types who have something to prove or a job to claim. Pete Alonso’s 1.006-OPS spring last season is a great example of this, not because the raw stats themselves said something, but rather that they helped persuade the New York Mets to put him on their Opening Day roster. Another statistical factor to consider is whether a player’s strikeout or walk rates has noticeably shifted from previous seasons, such as when Lance Lynn struck out 22 batters in 16 2/3 spring innings, perhaps hinting at what was to come in 2019.
6. Go bargain-shopping for saves
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, 41% 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 standouts Ian Kennedy, Taylor Rogers, Hector Neris, Liam Hendriks, Hansel Robles and Emilio Pagan. Another 6% of the league’s saves came from pitchers whose ADPs were between 301-450, meaning that nearly 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. Especially the deeper the player pool your league uses — think AL- and NL-only — the more likely 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 2019 where more and more teams are shifting towards committee closer strategies.
7. Resist the recency bias
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.
The recency bias can reveal itself with the one-year wonder, such as the aforementioned Hudson but also in the contrasting case of Khris Davis, who had a miserable year that was marred by injuries for a good four-plus months. In Davis’ case, it’s important to account for the effect of his injuries on his performance, while not forgetting the rather-productive three 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. By April 15 of last season, fantasy managers who fell for early small samples might’ve believed in Freddy Galvis’ .339 batting average and five home runs, or Carlos Rodon’s two wins and 3.27 ERA, or that Charlie Blackmon (.221 AVG, 0 HR) was done as an elite Coors Field performer.
Be patient, especially early in the year, because baseball tends to even out the larger the period of time you’re examining.
8. Resist the rookie hype
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 recent standouts as Aaron Judge and the aforementioned 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.
The problem with rookie-chasing, though, is that for every Judge or Acuna, there’s an Alex Reyes, Nick Senzel or Forrest Whitley, 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 do have 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.
Senzel, for example, fits the description of a “post-hype sleeper”: A player who still possesses similar talent to the scouting reports at the time of his debut, but who required more time to emerge in a prominent role and adapt to big-league pitching. He’ll also turn 25 in June, which is often considered the heart of a player’s prime (that can extend anywhere from ages 23 to 29). Remember, one of the goals in fantasy baseball is to unearth value where your competition least expects it. In Senzel’s case, his price tag is going to be considerably lower now than where it was a year ago at this time, but now everyone is going to want Luis Robert, 2020’s hottest rookie.
That’s not to say that Senzel is a better pick than Robert, but considering Senzel’s ADP is 242nd overall and Robert’s 111th, there’s a case to be made that getting Senzel at closer to his ADP is better than taking Robert’s at or sooner than his. Steamer’s projections, after all, have Senzel batting .261 with 14 homers and 14 stolen bases in 476 trips to the plate, and Robert batting .272 with 24 homers and 20 steals in 533 plate appearances.
9. Have patience through streaks — if the player’s skill set warrants
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 a home run, strikeout or walk, represent the streakiest around. The king of “three true outcomes” is Joey Gallo, who through the first five seasons of his big-league career has seen 59.3% of his plate appearances end in a home run, strikeout or walk. Sure enough, in a 2019 that was abbreviated by injuries, he had a month during which he swatted 10 home runs with 25 RBIs (March/April), and another month during which he batted .135 and struck out in 31 of his 59 trips to the plate (July, before he got hurt).
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. Mike Fiers is an excellent example of this. A pitcher with a career 20.9% strikeout rate (and 18.4% during his Oakland Athletics career), Fiers carried a 6.81 ERA into his ninth start of the 2019 season, on May 7. If this story sounds familiar, it should: He threw a no-hitter that night, beginning a 17-start stretch during which time he had 15 quality starts, 10 wins and a 2.12 ERA.
In Fiers’ 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 greater effort to find replacements to fill in the gaps between their cold spells.
Always consider the nature of the player, what his skills tell you — when Max Scherzer begins his 2019 with three losses and a 4.45 ERA in five starts, be patient! Even in a year where he dealt with some injuries, he nevertheless gave you a 2.57 ERA and 199 strikeouts over 22 starts in the Washington Nationals’ final 140-or-so games last year.
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