The Playbook, Inning 8: Advanced stats to use for fantasy baseball

The Playbook, Inning 8: Advanced stats to use for fantasy baseball

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

Baseball is such a different game today than it was when rotisserie was
first invented.

Back in 1980, most anyone interested in baseball was lured in by such
“bubblegum card” numbers as batting average, home runs, wins and ERA. Over
the years, the brightest minds in the game brought to light the fact that
there were better ways to evaluate baseball players.

Today, we’ve got so many statistics to choose from that even advanced
fantasy players might find themselves confused. Even turning on a broadcast
might sometimes seem daunting, with recent statistical innovations as Exit
Velocity, xwOBA or FIP casually being tossed about. Which of these matter
for our purposes? And, perhaps more importantly, what the heck do some of
these stats even mean?

Regardless of your experience level in fantasy baseball, a refresher (or
primer for the newbies) can be immensely helpful. This edition of the
Playbook dives deeper into some of the more modern metrics we use to
evaluate players. They are separated into several different statistical
categories below.

Statcast

The PlaybookInning 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: Adjusting to league trends Inning
8: Utilizing advanced stats Inning 9: Mastering the player pool

It has been all the rage in baseball analysis, fantasy baseball and even
television broadcasts during the past half-decade, but what, exactly, is Statcast?

Statcast is a data-tracking and collection tool that analyzes players’
skills, which began on a partial trial basis in 2014 and came to all 30
big-league stadiums in 2015. Initially, it used a combination of camera and
radar systems, but in 2020, a sophisticated camera system called Hawk-Eye
was installed in every big-league stadium, with 12 such cameras now in
place at each venue. This data, in full, is only available for the past
nine seasons (2015-23). MLB.com’s Statcast glossary provides more detailed information on how the system works, for those
interested, but to summarize for fantasy purposes, Statcast provides us a
way of scouting players by converting players’ raw abilities into
statistics.

The easiest place to find Statcast data, in an easily sortable format, is
on BaseballSavant.com. There, you’ll find leaderboards, reports on full player statistics, a
search engine, individual player pages and a scoreboard that allows you to
track player performance in real-time, among other tools.

Here are some of the key, fantasy-relevant Statcast metrics:

Exit Velocity (EV): This measures how fast, in miles per hour, a batted ball was hit by a
batter. Ultimately, the harder a batter hits a ball, the less time the
defense will have to react and the further it is likely to travel, both of
which increase the chances of a positive result for the hitter. Therefore,
when this metric is used to evaluate pitchers, lower numbers are more
desirable.

A player’s Exit Velocity is most often referred to by the average of this
number over all of what Statcast calls “Batted Ball Events,” or batted
balls in play, which is his Average Exit Velocity (aEV). The league’s Average Exit Velocity in 2023 was 88.5 mph, and it took a
92.0 mph number for a player to place in the 90th percentile, with 86.6 mph
placing him in the 10th percentile.

These were the top 10 in aEV among batting title-eligibles in 2023:

Ronald Acuna Jr., 94.7 mphShohei Ohtani, 94.4Matt Olson, 93.7Matt Chapman, 93.4Yandy Diaz, 93.4Corey Seager, 93.3Juan Soto, 93.2MJ Melendez, 93.2Rafael Devers, 93.1Julio Rodriguez, 92.7

J.D. Martinez (93.4) and Yordan Alvarez (93.3) were 23 and six plate appearances shy, respectively, from reaching
batting title eligibility. Note that Statcast’s leaderboard sets its
qualification threshold by the number of “batted ball events,” rather than
plate appearances.

These were the bottom 10 in aEV among eligible hitters:

Andres Gimenez, 84.8 mphWhit Merrifield, 85.1Thairo Estrada, 85.9Steven Kwan, 86.0Jeff McNeil, 86.0Ha-Seong Kim, 86.2Myles Straw, 86.3Dominic Smith, 86.3Nico Hoerner, 86.6Andrew Benintendi, 86.6

Esteury Ruiz (82.7) would have easily topped this list, but he finished five plate
appearances shy of qualifying for the batting title.

Shifting to the pitchers, among the 127 who worked at least 100 innings
last season, these were the top 10 in aEV allowed:

Nick Martinez, 84.7 mphKyle Hendricks, 85.2Shohei Ohtani, 86.4Corbin Burnes, 86.4Michael King, 86.8Zack Wheeler, 86.9Tyler Anderson, 87.0Pablo Lopez, 87.1Blake Snell, 87.2Paul Blackburn, 87.2

Conversely, these were the 10 worst pitchers in the category:

Shane Bieber, 91.6 mphFramber Valdez, 91.5Zac Gallen, 91.5Andrew Abbott, 91.2Taj Bradley, 91.2Brady Singer, 91.0Griffin Canning, 91.0Hunter Brown, 90.8Reese Olson, 90.8Ryne Nelson, 90.8

Launch Angle (LA): This measures the vertical angle at which a batted ball leaves a hitter’s
bat. A Launch Angle of zero degrees means that the ball left the bat
parallel to the ground, while a 90 degree result would mean that the ball
went straight up off the bat. As with Exit Velocity, Launch Angle is most
commonly referred to by its average (aLA).

Launch Angle is one way that we can determine the type of batted ball, when
examined individually. For example, a Launch Angle beneath 10 degrees is
generally regarded as a ground ball, 10-25 degrees is considered a line
drive, 25-50 degrees a fly ball and anything greater than 50 degrees a
pop-up. Using averages, players with higher launch angles are generally
classified as fly ball hitters (or pitchers), while those with lower launch
angles are termed ground-ball hitters (or pitchers).

There were the top 10 batting title-eligible hitters in terms of average
Launch Angle last season, along with their ranking in terms of fly ball
rate:

Jack Suwinski, 22.4º aLA, 36.3 FB% (3rd)Isaac Paredes, 22.2º aLA, 28.5 FB% (47th)Max Muncy, 21.7º aLA, 38.5 FB% (1st)Mookie Betts, 20.6º aLA, 35.7 FB% (5th)Daulton Varsho, 20.5º aLA, 31.1 FB% (26th)Cal Raleigh, 20.3º aLA, 35.1 FB% (8th)Anthony Santander, 20.2º aLA, 32.5 FB% (18th)Francisco Lindor, 19.2º aLA, 31.4 FB% (24th)Marcus Semien, 19.1º aLA, 35.4 FB% (6th)Kyle Schwarber, 19.0º aLA, 33.8 FB% (14th)

Next, here were the bottom 10 in Launch Angle:

Tim Anderson, 2.0º aLA, 10.7 FB% (lowest)Christian Yelich, 3.5º aLA, 17.3 FB% (second-lowest)DJ LeMahieu, 3.8º aLA, 17.4 FB% (third-lowest)Masataka Yoshida, 3.9º aLA, 19.4 FB% (10th-lowest)William Contreras, 4.7º aLA, 20.4 FB% (17th-lowest)Orlando Arcia, 5.4º aLA, 20.8 FB% (20th-lowest)Jeremy Pena, 5.5º aLA, 18.9 FB% (eighth-lowest)Yandy Diaz, 5.7º aLA, 20.8 FB% (19th-lowest)Maikel Garcia, 6.1º aLA, 18.3 FB% (sixth-lowest)Bo Bichette, 6.2º aLA, 18.8 FB% (seventh-lowest)

Again using 100 innings pitched as our qualification threshold, here were
the 10 pitchers with the lowest average Launch Angles in 2023, along with
their fly ball rates:

Logan Webb, 0.6º aLA, 14.9 FB% (lowest)Alex Cobb, 1.3º aLA, 16.3 FB% (third-lowest)Marcus Stroman, 3.0º aLA, 16.2 FB% (second-lowest)Framber Valdez, 4.2º aLA, 18.5 FB% (fifth-lowest)Brayan Bello, 4.9º aLA, 20.4 FB% (ninth-lowest)David Peterson, 5.3º aLA, 17.2 FB% (fourth-lowest)Tyler Glasnow, 5.8º aLA, 23.2 FB% (27th-lowest)Nathan Eovaldi, 6.4º aLA, 21.4 FB% (15th-lowest)Nick Martinez, 6.4º aLA, 20.6 FB% (11th-lowest)Tanner Houck, 6.5º aLA, 20.8 FB% (12th-lowest)

Here were the 10 pitchers who had the highest average Launch Angles:

Cristian Javier, 23.8º aLA, 38.8 FB% (highest)JP Sears, 22.6º aLA, 35.4 FB% (fourth-highest)Andrew Abbott, 21.6º aLA, 35.7 FB% (second-highest)Mike Clevinger, 21.4º aLA, 33.8 FB% (10th-highest)Tyler Wells, 20.7º aLA, 35.2 FB% (fifth-highest)Kutter Crawford, 20.4º aLA, 31.9 FB% (15th-highest)Joe Ryan, 20.4º aLA, 34.7 FB% (eighth-highest)Max Scherzer, 20.2º aLA, 32.7 FB% (13th-highest)Bailey Ober, 20.0º aLA, 35.2 FB% (sixth-highest)Jordan Lyles, 19.8º aLA, 33.0 FB% (12th-highest)

Hard Hit Rate: This one takes Exit Velocity one step further, designating a “Hard Hit”
batted ball as one that was struck with an exit velocity of at least 95
mph, then taking the player’s average of all batted balls that were hit at least that speed. Again, MLB.com’s Statcast glossary has more details on the methodology, including the rationale for that
number, but to summarize, it’s at the 95 mph threshold when a batted ball’s
potential result improves dramatically.

While Exit Velocity can help with predictive — meaning, for us, fantasy — analysis, Hard Hit
Rate is a better tool, extracting only the rate of the most positive, and
productive, results. There’s a stronger correlation between high Hard Hit
Rates among hitters or low ones among pitchers and fantasy success.

Among batting title-eligible hitters in 2023, here were the top 10 in Hard
Hit Rate:

Matt Chapman, 56.4%Matt Olson, 55.5%Juan Soto, 55.3%Ronald Acuna Jr., 55.2%Rafael Devers, 55.1%Shohei Ohtani, 54.2%Yandy Diaz, 54.0%Corey Seager, 53.2%Gunnar Henderson, 52.0%Julio Rodriguez, 52.0%

These 10 names comprised three of the six hitters who hit at least 40 home
runs (Olson, Ohtani and Acuna), and the group averaged 34 homers. Eight of
the 10 finished among the top-25 hitters in either fantasy points scored or
on the ESPN Player Rater (Olson, Soto, Acuna, Devers, Ohtani, Diaz, Seager and Rodriguez).

Taking the opposite approach, here were the bottom 10 qualifiers in Hard
Hit Rate:

Steven Kwan, 18.8%Myles Straw, 23.3%Whit Merrifield, 24.3%Luis Arraez, 25.7%Ha-Seong Kim, 26.7%Andres Gimenez, 27.0%Andrew Benintendi, 27.0%Jeff McNeil, 27.4%TJ Friedl, 27.6%Isaac Paredes, 28.5%

Sticking with the 100-inning pitching qualification threshold, here were
the 10 best pitchers in terms of Hard Hit Rate in 2023:

Nick Martinez, 29.9%Wade Miley, 31.3%Kyle Hendricks, 31.5%Tyler Anderson, 32.3%Corbin Burnes, 32.4%Paul Blackburn, 33.2%Michael King, 33.3%Drew Smyly, 33.6%Blake Snell, 33.8%Julio Urias, 34.5%

Conversely, here were the 10 worst pitchers in Hard Hit Rate:

Brady Singer, 48.6%Shane Bieber, 47.8%Taj Bradley, 46.4%Adrian Houser, 46.3%Zac Gallen, 46.2%Logan Webb, 46.0%Framber Valdez, 45.6%Braxton Garrett, 45.1%Tyler Glasnow, 44.6%Logan Gilbert, 44.6%

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Barrels: Another “one step further” metric, this time combining Exit Velocity and
Launch Angle, Barrels are defined as batted balls hit at the optimal marks
in both of those categories. Statcast specifically classifies these as
batted balls that, when combining those two factors, have resulted in a
minimum .500 batting average and 1.500 slugging percentage — in short,
they’re the big hits, and probably home runs. MLB.com’s Statcast glossary
delves a little deeper into the category here.

Barrels can be helpful when trying to judge players’ power (or the ability
to rein it in, on the pitching side), especially if trying to remove park
factors from the mix. Hitters who do well in the category typically fare
well in the home run department, as eight of the 13 who managed at least 60
Barrels in 2023 also hit at least 30 home runs (a level that only 29
hitters reached), while all six hitters with at least 66 Barrels hit
37-plus homers (a level that only 11 hitters reached).

Here were the top 10 in Barrels, along with their homer totals and ranks:

Ronald Acuna Jr., 86 Barrels, 41 home runs (fifth)Matt Olson, 73 Barrels, 54 homers (major league leader)Shohei Ohtani, 70 Barrels, 44 (fourth)Aaron Judge, 66 Barrels, 37 homers (tied for 10th)Marcell Ozuna, 66 Barrels, 40 homers (sixth)Austin Riley, 66 Barrels, 37 homers (tied for 10th)Pete Alonso, 62 Barrels, 46 homers (third)Adolis Garcia, 62 Barrels, 39 homers (tied for seventh)Spencer Torkelson, 62 Barrels, 31 homers (tied for 22nd)Kyle Schwarber, 61 Barrels, 47 homers (second)Bobby Witt Jr., 61 Barrels, 30 homers (tied for 26th)

To repeat, this is a metric that can also be used to evaluate pitchers.
Among ERA qualifiers, Corbin Burnes, Justin Steele and Zack Wheeler tied for the fewest Barrels allowed last season (27), while Miles Mikolas surrendered a league-most 66. Steele’s 0.73 HR/9 ratio, unsurprisingly,
was second-best among those 44 ERA qualifiers, while Mikolas’ 1.16 HR/9
ratio was 15th-highest among that same group. That said, and to illustrate
that this, nor any, category should be considered a “be all, end all” for
skills analysis, Burnes (1.02 homers per nine) and Wheeler (0.94) were more
middling in the rankings.

Mikolas, incidentally, had the majors’ seventh-lowest HR/FB% among those
same qualifiers (8.6%). That he made 21 of his 35 starts (60%) in the
game’s 10 least homer-friendly ballparks, not to mention another four in
venues that leaned on that side of the league’s average, surely helped keep
his home run total from spiraling out of control.

Spin Rate (SR): This measures the rate of spin on the baseball after a pitcher releases
it, calculated in revolutions per minute. In addition to velocity, a
pitcher’s Spin Rate has a bearing on its movement. For example, a fastball
thrown with high spin crosses the plate at a higher plane than one with low
spin, which is what causes the mythical “rising fastball.” Higher spin
rates, too, create more break on a pitcher’s curveball, improving its
effectiveness.

That’s not to say that Spin Rates on either extreme of the spectrum always result in a boost in pitch effectiveness.

Eury Perez, one of 2023’s rookie sensations, had a Spin Rate of 2,635 revolutions per
minute on his four-seam fastball, second-highest among pitchers who threw
at least 500 total pitches, behind only Ryan Helsley’s 2,642. Perez’s fastball averaged 97.5 mph, fourth-fastest among 94
pitchers who threw as many as he did, but batters hit .289 and slugged .585
against the pitch, placing him 11th-worst among those 94 in wOBA (.399).

Among the reasons were Perez’s extreme reliance upon the pitch — he threw
it 45.4% of the time, despite positively filthy metrics with his slider,
curveball and changeup — in part as the Miami Marlins aimed to ease the stress on his arm while keeping his innings in check,
but also because he leaned heavily upon the fastball when in hitters’
counts. In those situations, Perez surrendered a .615 wOBA with his
fastball, second-worst among pitchers who threw at least as many fastballs
as he did in those counts. It’s not an unfair assumption to surmise that
hitters adopted a “sit on the fastball” approach with Perez, which could
explain why he had such a disparity in performance between his fastball and
secondary pitches.

Nevertheless, Perez’s fastball results illustrate that the Spin Rate metric
— nor average velocity, on its own — isn’t the solitary indicator of an
elite pitch.

Robert Stephenson’s cutter, a pitch that he introduced into his repertoire in 2023, presents
an ideal example of a pitch made more effective thanks to its high spin
rate. Among any pitch thrown by an individual at least 250 times last
season, his cutter had the most revolutions per minute of that specific
pitch type (2,874), a rate that compared with some of the higher spin rates
among curveballs or sliders, pitchers that typically generate high spin
rates (often in the ballpark of 3,000 revolutions per minute).

Stephenson’s cutter was responsible for 42 of his 77 total strikeouts,
generated a 60% miss rate on hitters’ swings, and afforded hitters only a
.101 batting average against it. Statcast graded the pitch as worth 12 runs
above average, making it one of the league’s most effective pitches overall
on a per-pitch basis. It was a huge contributor to what was a breakthrough
year for the right-hander, earning him a three-year, $33 million free agent
contract this winter from the Los Angeles Angels, who might even give him an opportunity to serve as their closer.

Expected Batting Average (xBA), Expected Slugging Percentage (xSLG) and
Expected Weighted On-Base Average (xwOBA): These might be the most helpful for fantasy managers, and definitively
wiser metrics for stripping “luck” factors from players’ numbers. Each
formulates an expected number based on the Exit Velocity, Launch Angle and,
if applicable based on the type of batted ball, the player’s Sprint Speed,
providing a better gauge of what the player should’ve been expected to do,
either on an individual play or over the season (if the cumulative numbers).

Expected Weighted On-Base Average should be of more interest to those of
you in points-based leagues, which reward for doubles and triples. It helps
provide a fuller picture of a player’s hitting ability.

Here were the top 10 qualified hitters in terms of xwOBA in 2022, along
with their finishes among hitters in fantasy points:

Ronald Acuna Jr., .461 xwOBA, 707 fantasy points (first)Shohei Ohtani, .427 xwOBA, 490 FPTS (eighth)Corey Seager, .412 xwOBA, 443 FPTS (15th)Freddie Freeman, .408 xwOBA, 568 FPTS (fourth)Juan Soto, .408 xwOBA, 516 FPTS (seventh)Mookie Betts, .407 xwOBA, 574 FPTS (second)Bryce Harper, .399 xwOBA, 356 FPTS (57th)Marcell Ozuna, .396 xwOBA, 405 FPTS (29th)Matt Olson, .392 xwOBA, 571 FPTS (third)Kyle Tucker, .386 xwOBA, 524 FPTS (fifth)

If we adjusted the qualification threshold down to 450 plate appearances,
then Aaron Judge (.461 xwOBA) and Yordan Alvarez (.438) would sandwich Acuna as the top three on the leaderboard, and Judge
(340 FPTS) and Alvarez (388 FPTS) had plenty productive fantasy seasons in
their own right.

One hitter who finished high on the xwOBA leaderboard, but whose raw
fantasy numbers didn’t mirror it, was Vladimir Guerrero Jr.. His .375 xwOBA greatly exceeded his .340 actual wOBA, resulting in a 35
point differential that was the widest in that direction among qualified
hitters. Considering it was the first time in his five big-league seasons
that he had an actual wOBA beneath his xwOBA, while logging relatively
similar hard-contact metrics, he should be expected to enjoy better fortune
on his balls in play in 2024 than he did in 2023.

These categories can also be used to identify regression candidates,
players whose batted-ball outcomes were more favorable than they should’ve
been. Friedl, mentioned above regarding his lack of hard contact, had the
majors’ largest wOBA-xwOBA split among qualified hitters, 64 points in that
direction (.353 wOBA, .289 xwOBA).

Here is an excellent place to find all of these expected statistics, as well as
some of the other Statcast offerings, including a CSV download option. You
can also find the numbers for pitchers here.

Sprint Speed: Introduced in 2017, this measures, in feet, how quickly a player ran
during the fastest one-second window of his running the bases. Two types of
baserunning opportunities are measured: Runs to first base on weakly hit
grounders, or runs of two bases or more on balls kept within the park
(excluding runs from second base on an extra-base hit). This helps get a
sense of a player’s raw speed, something that can be useful when seeking
stolen-base production in fantasy.

Any run measured at greater than 30 feet per second is judged excellent and
termed a “Burst,” and the league’s average number in the category is
usually only a little better than 27 feet per second. Slower runners
sometimes see numbers as poor as 22 feet per second, such as Yasmani Grandal, who averaged a worst-in-baseball (among those with at least 50 measured
runs) 22.8 feet per second in 2023.

These were the top 10 performers in Sprint Speed in 2023, among those who
had at least 50 “competitive runs” measured, along with their stolen base
totals:

Elly De La Cruz, 30.5 feet/second, 35-of-43 stealing basesBobby Witt Jr., 30.5 feet/second, 49-of-64 stealing basesDairon Blanco, 30.3 feet/second, 24-of-29 stealing basesTrea Turner, 30.3 feet/second, perfect 30-of-30 stealing basesJorge Mateo, 30.1 feet/second, 32-of-37 stealing basesCorbin Carroll, 30.1 feet/second, 54-of-59 stealing basesBlake Perkins, 30.0 feet/second, 5-of-7 stealing basesJacob Young, 30.0 feet/second, perfect 13-of-13 stealing basesJake McCarthy, 29.9 feet/second, 26-of-30 stealing basesBrenton Doyle, 29.9 feet/second, 22-of-27 stealing bases

As you can see, this group went a combined 290-of-339 stealing bases, for
an 85.5% success rate that easily exceeded the league’s average (80.2%).

There are plenty of other Statcast categories you can investigate, but
these are the seven that have the most immediate relevance to fantasy
managers.

Defense independent pitching metrics

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FIP and xFIP: An abbreviation for Fielding Independent Pitching score — and for
expected FIP — this attempts to eliminate the influence of a pitcher’s
defense upon his statistics, by judging him on only his home runs, walks
and hit batsmen allowed and his strikeouts and whittling those down to a
number similar to ERA. xFIP takes it a step further, removing the “luck”
factor involved with home runs by instead using the pitchers’ fly balls
allowed and assuming a league-average home run rate on them.

FIP can be a quick, basic way of stripping any misfortune a pitcher faced
during the season in question, identifying pitchers whose fortunes should
even out in the future. xFIP, meanwhile, can be helpful when evaluating
pitchers assigned to pitch in ballparks with significantly different park
factors, or for those changing teams. Whichever you use, both are
substantially stronger scouting measures than ERA.

These were the top 10 pitchers in FIP in 2023, among those who worked at
least 100 innings pitched, all of whom had excellent seasons:

Sonny Gray, 2.83Spencer Strider, 2.85Tyler Glasnow, 2.91Kevin Gausman, 2.97Zach Eflin, 3.01Justin Steele, 3.02Michael King, 3.13Zack Wheeler, 3.15Logan Webb, 3.16Gerrit Cole, 3.16

Comparing a pitcher’s FIP to his ERA is often a handy, albeit basic, way of
unearthing “flukes” who might be in line for better fortune in the year
ahead. Again among pitchers who threw at least 100 innings, here were the
eight widest ERA-FIP differentials, leaning on the side of their having
experienced more misfortune:

Adam Wainwright, 1.41 run difference (7.40 ERA, 5.99 FIP)Brady Singer, 1.24 (5.52, 4.29)Joey Wentz, 1.09 (6.90, 5.81)Spencer Strider, 1.00 (3.86, 2.85)Dylan Cease, 0.85 (4.58, 3.72)Luke Weaver, 0.80 (6.40, 5.61)Taj Bradley, 0.80 (5.59, 4.79)Hunter Brown, 0.71 (5.09, 4.37)David Peterson, 0.69 (5.03, 4.34)Jordan Lyles, 0.66 (6.28, 5.62)

That’s not to say that Weaver is destined for a major rebound in 2024,
especially since a 5.61 FIP is anything but a pretty number. Cease’s
inclusion on the list, however, indicates that he pitched much better than
his raw fantasy numbers indicated.

Flipping things around, here are the 10 pitchers who were most fortunate in terms of their ERA-FIP differential:

Clayton Kershaw, minus-1.57 run difference (2.46 ERA, 4.03 FIP)Wade Miley, minus-1.55 (3.14 ERA, 4.69 FIP)Tyler Wells, minus-1.34 (3.64 ERA, 4.98 FIP)Javier Assad, minus-1.24 (3.05 ERA, 4.29 FIP)Blake Snell, minus-1.19 (2.25 ERA, 3.44 FIP)Michael Kopech, minus-1.04 (5.43 ERA, 6.46 FIP)Josiah Gray, minus-1.03 (3.91 ERA, 4.93 FIP)Shohei Ohtani, minus-0.86 (3.14 ERA, 4.00 FIP)J.P. France, minus-0.83 (3.83 ERA, 4.66 FIP)Jake Irvin, minus-0.69 (4.61 ERA, 5.30 FIP)

Beware of putting too much stock into FIP and xFIP, however, with my recommendation to consider
it merely another evaluative tool in your toolbox. Miley, for example, now
has an ERA-FIP differential of at least half of a run in each of his last
three healthy seasons (2019, 2021 and 2023), exhibiting a tendency to
outperform his peripherals thanks to his control and his ability to
minimize hard contact.

SIERA: An abbreviation for Skill-Interactive ERA, SIERA is a more recent
innovation that, like FIP, attempts to remove defensive influence from the
pitching equation and determine just how effective said hurler actually
was. The key difference between SIERA and FIP is that while the latter
excludes batted balls from its equation, the former does consider them in
the calculation. If you’re interested in the mathematical details,
FanGraphs wrote a great column explaining SIERA and providing the formula
to calculate it here.

While SIERA’s leaderboard doesn’t precisely match that of FIP, it does a
good job of identifying pitching skill. Here were the top 10 in SIERA in
2023, using the 100-inning threshold for qualification:

Spencer Strider, 2.86Tyler Glasnow, 3.08Logan Webb, 3.16Michael King, 3.29Zach Eflin, 3.30Kevin Gausman, 3.34Nick Pivetta, 3.36Pablo Lopez, 3.37Joe Ryan, 3.44Freddy Peralta, 3.45

Luck’-based statistics

Once the hottest thing in fantasy baseball analysis, luck-based stats have
taken more of a backseat in recent seasons, as we gain greater awareness of
the ingredients that influence them. Still, it’s worth a quick refresher on
these, as each can provide a small insight into a player’s ability, not to
mention our understanding of them can reveal the pitfalls involved in
trusting each too much.

BABIP, or Batting Average on Balls in Play: First introduced by Voros McCracken
around the turn of the century, BABIP measures a pitcher’s ability to
prevent hits on balls in play, as well as a hitter’s success rate only on
the batted balls he puts into play. This removes walks, strikeouts and home
runs — those don’t land within the field of play, after all — from the equation. You can calculate it
yourself by dividing hits minus home runs by at-bats minus home runs minus
strikeouts plus sacrifice flies, or (H – HR)/(AB – HR – K + SF).

The idea is that the league’s average BABIP is generally around .300, so
any player with a number significantly removed from that is likely to
regress towards said average in the near future. As defensive shifts took
hold over the past decade, however, that number inched downward. In both
2020 and 2021, the league’s average BABIP was .292, and in 2022, it dipped
to .290, the league’s lowest rate in 30 years. With new rules in place
governing shifts in 2023, however, the league’s BABIP rebounded to .297.

The problem with BABIP as an analytic tool is that it completely ignores
both the quality of contact involved with the type of batted ball, as well
as the defensive alignment, things that the aforementioned Statcast
“expected” statistics aim to correct. That’s why, when examining BABIP,
it’s wise to account for the type of pitcher or hitter (ground ball versus
fly ball), as well as the player’s own history in the category. For
example, has he routinely posted BABIPs that exceed the league’s average?

In 2023, the top two qualified hitters in terms of BABIP were Freddie Freeman (.370) and Yandy Diaz (.367), numbers that were 29 and 54 points higher than their career rates
in the category entering the season. That comparison hints that some batting average regression should be anticipated with either hitter in
2024. It’s fair to point out, however, that Freeman has now managed a
.350-plus BABIP in six of his past 10 seasons, while Diaz had a .371 BABIP
in limited time in 2018 as well as a .323 number in the category as a
regular in 2022, meaning neither should be expected to see his BABIP completely regress to the league’s average rate.

Home Run per Fly Ball Percentage (HR/FB%): Alluded to in the xFIP section, Home Run per Fly Ball Percentage
determines how fortunate a player might have been in seeing the fly balls
he hit clear the outfield fence for a home run. The league’s annual average
in the category varies more than does BABIP, but in 2023 was 10.6% —
nearly a full percentage point better than 2022’s rate (9.7%). Like BABIP,
hitters and pitchers are typically expected to regress towards the mean in
the near future, though unlike BABIP, this category can be much more easily
influenced by things such as contact quality or park factors.

In 2023, Lance Lynn (13.8%) had the highest qualified rate among pitchers, while Logan Webb, who finished second in NL Cy Young balloting, had a career-high, and
third-worst-in-the-league 13.2% rate in the category. Sonny Gray had the majors’ lowest rate (5.5%), while Cristian Javier had a third-best 8.3% rate that suggested his second-half swoon could have
been much worse than it was.

One big pitfall to consider with this category is the differing
calculations across statistical sources, due to the different
classifications in batted ball types as well as the slight differences in
formulas. For example, FanGraphs had the league’s average Home Run per Fly
Ball Percentage as 12.7%.

Strand Rate, or Left On Base Percentage (LOB%): This measures the percentage of base runners that a pitcher leaves on base
in a given outing, or over the course of a season. Rather than taking the
actual number of baserunners stranded, it assumes that runners score at a
league-average rate. The formula is hits plus walks plus hit batsmen minus
runs scored, divided by hits plus walks plus hit batsmen minus home runs
times 1.4 (a predetermined, league-average factor), or (H + BB + HB – R)/(H
+ BB + HB – (HR * 1.4)).

The league’s average Strand Rate is typically around 72.0%, and in 2023 it
was 71.9%. Last season among ERA-qualified pitchers, Blake Snell was the leader in the category (86.7%), while Jordan Lyles (56.3%) brought up the rear. Snell’s Strand Rate was eerily similar to the
88.0% number he put forth the last time he won the league’s Cy Young Award
(2018), heightening concerns that he’ll regress in 2024.

Site-to-site variance

Not every batted ball is judged the same.

As mentioned in the Home Run per Fly Ball Percentage category, the
classification of batted balls in play can have a noticeable influence upon
the results. For example, both Statcast and our internal pitch-tracking
tool assign pop-ups as their own category, independent of fly balls,
whereas FanGraphs’ listed fly ball rates include those pop-ups. Hard Hit
Rates also can vary depending upon your source.

For example, Isaac Paredes had the majors’ highest pop-up rate among batting title-eligible hitters,
having popped the ball up 14.9% of the time that he put it into play.
FanGraphs includes these in his fly ball rate, which is how he had a 47.0%
number there, 11th-highest among 133 qualifiers, whereas he had a mere
28.5% fly ball rate per our internal pitch-tracking tool. This is an
especially important distinction for Paredes, who plays in one of the most
extreme pitching environments in all of baseball, Tampa Bay’s Tropicana
Field, as his modest fly ball rate will probably make it challenging for
him to repeat or even approach his 31 home runs from last year.

Always consider multiple sources with your data. Wide variance upon the
results might require additional research to determine the player’s true
skill level. If all else fails, though, I’d trust the Statcast data first
and foremost.

Where to research these numbers more deeply on your own

The PlaybookInning 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: Adjusting to league trends Inning
8: Utilizing advanced stats Inning 9: Mastering the player pool

Each of the aforementioned statistical categories is readily available on
the internet, including many download options for you to play with the
numbers yourself.

BaseballSavant.com, referenced earlier, houses a wide variety of Statcast
statistics that can be sorted, searched and downloaded. Some of the links
for those are available above, but I’m focusing on its Search page here, since it’s a great place with which to run queries of your
choosing while scouting players.

There, you’ll find all sorts of situations with which to examine facets of
a player’s game, including performance against different pitch types, in
certain counts, against players of either handedness, or using specific
date ranges, among many other options. Be sure to first select your Player
Type, batter (or specific position player) or pitcher, before entering your
query. To provide a specific example, if you’re interested in seeing which
hitter had the highest xwOBA during the final month of 2023, choose Player
Type batters, set the Game Date >= as 2023-09-01, then choose Sort By
xwOBA. You could also set a Min # of Results if you wish, say, 250.

As you can see, Ronald Acuna Jr. (.495) occupies the top spot using this split, while Elvis Andrus (.196) ranks last, perhaps one reason Andrus was still in search of a team
as spring training dawned.

Royce Lewis’ monstrous finish – he batted .313/.410/.612 with six home runs in 18
September games, plus his four additional home runs in the Twins’ six
postseason contests — help easily explain how he has been one of the more
popular breakthrough picks in early drafts.

FanGraphs is another site that offers custom statistics reports, including
those you can download. Here is where you can find the basic 2023 hitters’ leaderboard, but you can
select a variety of different reports: Standard statistics, Advanced
statistics, Batted Ball statistics, Win Probability and Value statistics,
+Stats (which compare the player’s performance to the league’s average),
Statcast statistics, Plate Discipline statistics, an entire array of
Pitch-Level Data that now resides under its own tab, and many other options.

As with Statcast, FanGraphs offers options to check players’ splits, as
well as to request numbers within a Custom Date Range. One example to
highlight some of the options is to check the standard stats page for
pitchers using the 2023 away-games split. There, you’ll see that Mitch Keller had a 5.35 ERA in his 18 starts away from Pittsburgh’s PNC Park, giving
him a near two-and-a-half-run differential between his home (2.90) and road
ERAs, the second-widest among qualifiers in that direction.

As a quick note, as FanGraphs isn’t a paywall website, especially in the
difficult current environment, consider ordering a membership to provide
your support.

Among some of the other websites you should consider in your scouting:

Brooks Baseball: Their strength is their Pitch F/X tool, which can help you do scouting on
players similar to some of those available on Statcast. There are options
to check player splits by situation and time period, and they have a
graphical interface that helps illustrate player skill findings.

Baseball Prospectus: They’ve been around for quite some time, providing analytics for well over
two decades as well as publishing an annual that profiles each player
individually. Many advanced analytics are available there as well.

Now that you’ve gotten your feet wet with advanced statistics, let’s put
them to use! The final inning of the Playbook extracts some of my favorite
findings using many of the tools discussed above.

Source: Tristan H. Cockcroft’s 9-part Playbook lays out how to go from fantasy baseball novice to expert in one season. Part 8 explains some of the advanced statistics available to the fantasy baseball manager and how to apply them correctly.