The Playbook, Inning 6: Nine must-follow tips

(The full, nine-inning Playbook was originally published in spring 2020. It has been updated for 2024 where applicable.)

By now, you might be fancying yourself a fantasy baseball pro.

You've read all five Playbook innings to date, and perhaps have even begun to craft your own cheat sheet for 2024. 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: Logan Webb had the third-best WAR among starting pitchers (5.5), trailing only Cy Young Award winners Gerrit Cole (7.4) and Blake Snell (6.0), the most total innings pitched (216), the second-most innings per start (6.5), the third-best ERA-qualified strikeout-to-walk ratio (6.3), and the seventh-best FIP, or Fielding Independent Pitching score (3.16). Unfortunately, due to his San Francisco Giants' issues scoring runs, as their 4.2 per-game average ranked 24th, Webb won only 11 times and had a losing record (11-13). Conversely, Taijuan Walker won four more games than Webb, despite turning in the seventh-worst qualified FIP (4.53) and averaging nearly a full inning less than Webb per start (5.6).

Batting average: Brandon Marsh hit a career-best .277 last season, 32 points greater than his 2022 number and his highest since he was in Double-A ball in 2019 (.300). It was also backed by a .397 BABIP, by far the majors' highest among hitters with at least 450 plate appearances and the highest by any player who met that qualification since 2019. Statcast said that, based upon Marsh's batted-ball distribution and quality of contact, he should've hit only .234. On the opposite side of things, Vladimir Guerrero Jr. hit just .264, the second-lowest number of his professional career behind only 2020's .262. Statcast, however, estimated that he should've hit .295, that expected batting average the ninth-best among the 133 hitters who qualified for the batting title.

ERA: Snell won the NL's Cy Young Award behind what was a major league-leading 2.25 ERA. That said, Statcast calculated that, based upon Snell's level of contact as well as quality of contact allowed, he should've had an ERA of 3.79 -- more than a run and a half higher than his actual number. Additionally, he became the first Cy Young Award winner in 64 years to lead the majors in walks, and his 13.3% walk rate became the second-highest in history for a league leader in ERA (King Cole, 1910). In contrast, Statcast had Joe Ryan sporting a better expected ERA (3.53) than Snell's, though Ryan's true ERA was 4.51.

Instead of weighting wins or ERA, use the aforementioned FIP, or SIERA (Skill-Interactive ERA) or Statcast's xERA. Simpler yet, trust the pitcher's WHIP over his ERA, or weight his K/BB 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.) Returning to Guerrero's example, as further evidence that his numbers should positively advance in 2024, Statcast reflected a 35 point wOBA-xwOBA (expected weighted on-base average) differential last season, fifth-widest among qualified hitters in the wrong direction (.340 wOBA, .375 xwOBA). He seemed particularly unfortunate on batted balls he put into play.

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.

To extract successful such examples from 2023, Kyle Schwarber, the No. 10 outfielder and No. 42 player selected overall on average in the preseason, hit .167/.312/.387 with 13 home runs through his first 58 games, for an average of 1.76 fantasy points per game that was well beneath the 2.29 he averaged from 2018-22. Fantasy managers who were aware at the time that he has a history of heating up beginning in June, however, could've reaped the rewards of a Schwarber trade around that time. From June 4 forward, he hit .213/.359/.520 with 34 homers while starting 102 of the Philadelphia Phillies' final 104 games, for an average of 2.92 fantasy points per contest.

On the "sell high" side, Jarred Kelenic, a then-23-year-old outfielder who was regarded one of the game's top prospects at the time of his 2021 debut, but struggled to adapt to the big leagues over parts of the previous two seasons, hit .297/.350/.564 with 10 home runs and six stolen bases in 45 games through May 22. At the time, he was averaging 2.44 fantasy points per game, significantly ahead of the aforementioned Schwarber. Considering Schwarber's then-30 years of age as well as Kelenic's spring adjustments that made his hot start seem legitimate, such a straight-up swap might've been entertained. Kelenic quickly cooled thereafter, hit .205/.291/.311 with one home run over his next 45 games, after which point he missed nearly two months of action due to a fractured foot suffered when he kicked a water cooler in frustration, limiting him to only 15 lackluster games upon his return in September.

Usually, fantasy managers who attempt the "buy low, sell high" strategy make a big mistake. 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 Schwarber away from his manager for a borderline roster-worthy player in an ESPN standard 10-team league -- with our new settings instituted in 2023, that'd be roughly the value of an outside-the-top-15 third baseman -- or to expect a top-25-overall-valued player in exchange straight up for Kelenic. No, the idea would have been to acquire Schwarber for anything noticeably cheaper than the "10th-most highly-regarded" outfielder on the date of the trade, or to trade Kelenic away for a player valued comparably to that same top-10 group of outfielders.

"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 20% of all starts last season resulted in a negative point total in ESPN standard points leagues, which was roughly the same percentage that were worth 18-plus points, 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 18 hitters to drive in at least 100 runs last season, 13 played for teams that ranked among the top 10 in terms of runs per game, and 11 of those 13 played for one of the six offenses that averaged greater than five runs per game. On the pitching side, three of the five pitchers to win at least 16 games last season pitched for teams that averaged at least five runs per game, while nine of the 12 pitchers to win at least 14 pitched for teams that were better-than-league-average in terms of run production.

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 2023 season, with the totals by the majors' best and worst from each spot.

You'll notice that the difference in plate appearances between each of the nine lineup spots is roughly 17 for each successive slot we move down; that's exactly the difference between the average team's Nos. 1 and 2 hitters last season. While 17 PAs might not seem like much over the course of a 162-game schedule, it nevertheless represents an opportunity advantage. The 123-PA difference between Nos. 1 and 8 hitters, meanwhile, is massive, which is why it was such a big deal when the Washington Nationals decided last July 7 to move CJ Abrams, up until then a 7-8-9 hitter, up into the leadoff spot, where he'd start in 71 of the team's final 75 games. Abrams averaged only 3.75 plate appearances per start before the move, compared to 4.54 after it, and bear in mind that came for a team that placed only 21st for the season in both runs scored and total plate appearances.

Hitters similarly slated for, or stuck in, bottom-third-in-the-order roles are at a significant disadvantage from an opportunity standpoint. That's increasingly true when the competitive levels of the offenses are unequal -- note the 136-PA difference between the best team's No. 2 and worst team's No. 7 hitter, an even wider margin than the aforementioned one between an average team's Nos. 1 and 8 hitters.

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, games in both states are 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 Mike Brosseau hit six spring home runs, second-most in the majors, and batted .387 with a 1.532 OPS, best among players with at least 30 plate appearances? You should, considering it happened just last year.

Nowhere is the absurdity of spring statistics more apparent than in the saves category. Over the last five full spring trainings (2018-19 and '21-23) -- we'll consider 2022's spring training "full" for argument's sake, despite its lockout-influenced abbreviation -- 15 pitchers had a three-save spring: Jonathan Aro, Ryan Brasier, Cody Carroll, Dietrich Enns, Caleb Freeman, Justin Hancock, Eric Hanhold, Nolan Hoffman, Andrew Kittredge, Jose Leclerc, Dominic Leone, Lucas Long, Riley O'Brien, James Teague and Hunter Wood. These pitchers went on to save a grand total of four big-league games during the regular seasons that followed, all four of them recorded by Leclerc last year. 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 can expect to see Devin Williams probably pitching the fifth, not the ninth, for the Milwaukee Brewers during spring training.

If there is a spring-stats angle worth exploiting, it's less-proven types who have something to prove or a job to claim. Anthony Volpe's .302/.413/.623 hitting line, three home runs and five stolen bases both underscored his multi-category, rotisserie-driven fantasy appeal and persuaded the New York Yankees to install him as the shortstop in their Opening Day lineup, something that wasn't guaranteed at the onset of spring training (remember, Oswald Peraza, who had a much more lackluster spring, was considered a prime competitor for the role as well).

Another statistical factor to consider is whether a player's strikeout or walk rates has noticeably shifted from previous seasons, such as when Mitch Keller, having added a cutter to his repertoire during the offseason, struck out 20 of the 61 spring batters he faced while walking only one, recapturing the promise that had made him one of baseball's top prospects at the time of his 2019 big-league debut. Keller would extend that success into the regular season, breaking out in a big way in the strikeout department (210) and finishing among his position's top 25 in fantasy points.

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, 39% of the majors' total saves last season came from pitchers who were unquestionably not drafted in ESPN leagues (specifically both outside the top 300 in ADP as well as selected in fewer than 5% of drafts), including 20-save performers Carlos Estevez, Adbert Alzolay, Will Smith and Trevor May. Note that this represented a sizable increase in the percentage of saves secured by the fantasy baseball "draftable" pool compared to 2022, but 39% is still a large portion of the saves market -- more than one-third -- that was widely available via free agency.

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. That the percentage of total saves amassed by the draftable pool tends to vary year over year makes it foolish to set an ironclad rule regarding the category.

Especially 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 with the recent, growing tendency of major league teams shifting to closer-by-committee 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 TJ Friedl, who despite good contact skills and batted-ball distribution had underlying metrics suggesting he'd have a tough time repeating 2023's top-100 overall fantasy performance, or Vinnie Pasquantino, whose 2023 ended in June due to a torn labrum in his right shoulder, casting some doubt on his ability to quickly rebound. Pasquantino, however, has an appealing combination of contact and raw power potential that could make him both a batting average and home run contributor, and it might take only a few strong spring games for us to evaluate whether he's back to 100%.

Another area where 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. Returning to the aforementioned Brandon Marsh example, through 40 days of the 2023 season, he might've convinced his fantasy managers that he was primed for a breakthrough, thanks to his .317/.413/.587 hitting rates. (His .446 BABIP at that point was second-highest in the majors.) Those same managers might've been panicking that Nolan Arenado's 32 years of age had finally come back to haunt him, as he was batting .232/.281/.324 with three home runs at that same seasonal stage.

Be patient, especially early in the year, because baseball tends to even out over 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 recent standouts as Pete Alonso, who set the single-season rookie record for home runs (53, in 2019), or Corbin Carroll, who became the first rookie in history to manage at least 25 home runs and 50 stolen bases (2023). Additionally, Ronald Acuna Jr., Michael Harris II, Gunnar Henderson, Julio Rodriguez, Spencer Strider and Fernando Tatis Jr. captured many a headline as rookies in recent years, while the graduation of several of the game's top prospects to the major leagues during the course of each of the past two seasons (Carroll and Henderson in 2022, Elly De La Cruz and Jasson Dominguez in 2023), fueled a perception that rookies are the "name of the game" nowadays.

The problem with rookie-chasing, though, is that for every Carroll or Rodriguez, there's a Brett Baty, Kyle Harrison or Andrew Painter, prospects who either got hurt, disappointed or took painfully long to get the call at all in 2023. 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.

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.

Schwarber could again serve as our example, as a major league-leading 53.9% of his plate appearances ended in either a home run, strikeout or walk last season, but to vary things up, let's examine the No. 2 name in that department, Jack Suwinski (51.1%). Suwinski was perhaps baseball's most inconsistent batting title-qualified hitter, beginning his season with a .297/.413/.656 stat line and six home runs in 21 games, only to follow it up with .141/.267/.219 rates and one homer in his next 20 contests. He then surged again, batting .257/.392/.629 with 12 homers in the following 36 contests, only to slump to the tune of .133/.261/.248 rates and two homers in his next 37. And for good measure, Suwinski batted .297/.365/.525 with five homers in his final 30 games. That's certainly a maddening pattern.

While one could attempt to use a hitter like Suwinski as a buy-low or sell-high candidate based upon where he's at on 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. Just as he was in this space last year, Drew Smyly remains an excellent recent example, in large part due to his injury history interrupting some of the better hot spells in his career. Smyly had a disastrous first start to 2023 (6 ER, 9 H, 4 2/3 IP), but won five of his next nine starts behind a 1.78 ERA. Things unraveled thereafter, his ERA 6.65 in his following nine turns, which earned him a demotion to the bullpen for most of the remainder of the year.

In Smyly'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 pitcher with the number of durability questions as he has -- 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 and what his skills tell you. Returning to Arenado's example, keep in mind that, after his aforementioned slow start to 2023, he roared back with .278/.327/.505 rates, 23 home runs and 75 RBIs in his final 109 games, much more in line with his previous two seasons' worth of production while with the St. Louis Cardinals. His overall level of career consistency warranted greater patience with him than with an average player, and his strong finish was representative of that.

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!