The Playbook, Inning 8: Advanced stats to use

(The full nine-inning Playbook was originally published in spring 2020. It has been updated for 2025 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

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 10 seasons (2015-24). 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 2024 was 88.8 mph, and it took a 92.0 mph number for a player to place in the 90th percentile, with 86.3 mph placing him in the 10th percentile.

These were the top 10 in aEV among batting title-eligibles in 2024:

Aaron Judge, 96.2 mph Shohei Ohtani, 95.8 Oneil Cruz, 95.5 Juan Soto, 94.2 Ketel Marte, 94.0 Vladimir Guerrero Jr., 93.8 Kyle Schwarber, 93.6 Rafael Devers, 93.2 Matt Chapman, 93.2 Yordan Alvarez, 93.1

Giancarlo Stanton (94.6 mph), Fernando Tatis Jr. (93.5) and Austin Riley (93.3), who all would have placed among the top 10 if they had the requisite plate appearances to qualify, fell 43, 64 and 33 PAs shy. Note, however, that Statcast's leaderboard sets its qualification threshold by number of "batted ball events," rather than plate appearances, meaning all three made their cut.

These were the bottom 10 in aEV among eligible hitters:

Sal Frelick, 83.4 mph Isaac Paredes, 85.0 Nico Hoerner, 85.7 Jacob Young, 85.8 Nolan Schanuel, 86.1 Daulton Varsho, 86.1 Steven Kwan, 86.3 Luis Arraez, 86.3 Nolan Arenado, 86.3 Andres Gimenez, 86.3

Several other players listed on Statcast's leaderboard, each of whom had 400-plus PAs, would have also placed highly on this list had they qualified for the batting title, including Jose Caballero (83.7 mph), Jake McCarthy (84.5) and Brayan Rocchio (84.6).

Shifting to pitchers, among the 126 who worked at least 100 innings last season, these were the top 10 in aEV allowed:

Michael King, 85.7 mph Kyle Hendricks, 85.9 Hunter Brown, 86.2 Max Fried, 86.3 Nick Martinez, 86.4 Zack Wheeler, 86.5 Blake Snell, 86.5 Chris Sale, 86.5 Justin Steele, 86.9 Michael Wacha, 86.9

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

Taj Bradley, 91.2 mph Patrick Corbin, 90.8 Kyle Harrison, 90.7 Trevor Rogers, 90.7 Casey Mize, 90.6 James Paxton, 90.5 Griffin Canning, 90.5 Jon Gray, 90.5 Carlos Rodon, 90.4 Colin Rea, 90.4

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:

Daulton Varsho, 24.2º aLA, 30.6 FB% (32nd-highest) Anthony Santander, 22.8º aLA, 33.8 FB% (13th-highest) Isaac Paredes, 22.4º aLA, 29.3 FB% (45th-highest) Mookie Betts, 21.4º aLA, 35.3 FB% (eighth-highest) Cal Raleigh, 21.2º aLA, 36.7 FB% (third-highest) Rhys Hoskins, 20.8º aLA, 36.6 FB% (fourth-highest) Willy Adames, 20.6º aLA, 36.4 FB% (fifth-highest) Jose Ramirez, 19.6º aLA, 31.1 FB% (28th-highest) Eugenio Suarez, 19.5º aLA, 33.3 FB% (15th-highest) Salvador Perez, 19.0º aLA, 33.8 FB% (12th-highest)

Next, here were the bottom 10 in Launch Angle:

Jacob Young, 2.0º aLA, 15.4 FB% (lowest) Brice Turang, 4.0º aLA, 17.7 FB% (third-lowest) Brendan Rodgers, 5.0º aLA, 16.9 FB% (second-lowest) Yandy Diaz, 5.0º aLA, 17.8 FB% (fourth-lowest) Maikel Garcia, 5.7º aLA, 20.4 FB% (10th-lowest) William Contreras, 6.1º aLA, 19.4 FB% (eight-lowest) Jackson Chourio, 7.2º aLA, 24.4 FB% (36th-lowest) Jeremy Pena, 7.4º aLA, 23.0 FB% (26th-lowest) Vladimir Guerrero Jr., 7.4º aLA, 21.2 FB% (14th-lowest) Luis Garcia Jr., 7.5º aLA, 25.1 FB% (42nd-lowest)

Again using 100 innings pitched as our qualification threshold, here were the 10 pitchers with the lowest average Launch Angles in 2024, along with their fly ball rates:

Jose Soriano, -1.1º aLA, 15.8 FB% (third-lowest) Framber Valdez, -0.2º aLA, 15.0 FB% (lowest) Andre Pallante, 1.0º aLA, 16.2 FB% (fifth-lowest) Cristopher Sanchez, 2.4º aLA, 15.6 FB% (second-lowest) Logan Webb, 2.4º aLA, 17.3 FB% (sixth-lowest) Max Fried, 2.7º aLA, 16.1 FB% (fourth-lowest) Tanner Houck, 3.5º aLA, 17.4 FB% (seventh-lowest) Ranger Suarez, 5.7º aLA, 18.2 FB% (eighth-lowest) Brayan Bello, 5.9º aLA, 19.6 FB% (10th-lowest) David Peterson, 7.0º aLA, 21.3 FB% (15th-lowest)

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

Joey Estes, 25.1º aLA, 35.0 FB% (third-highest) Nestor Cortes, 21.9º aLA, 32.1 FB% (11th-highest) Andrew Abbott, 20.7º aLA, 32.5 FB% (eighth-highest) Tyler Alexander, 20.2º aLA, 34.5 FB% (fourth-highest) Hunter Greene, 20.0º aLA, 31.7 FB% (13th-highest) Bailey Ober, 19.9º aLA, 35.2 FB% (second-highest) Kutter Crawford, 19.3º aLA, 32.3 FB% (ninth-highest) Nick Pivetta, 19.1º aLA, 32.1 FB% (10th-highest) Ryan Pepiot, 19.0º aLA, 29.0 FB% (35th-highest) Luis Gil, 19.0º aLA, 30.0 FB% (24th-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 2024, here were the top 10 in Hard Hit Rate:

Aaron Judge, 61.0% Shohei Ohtani, 60.1% Juan Soto, 57.0% Kyle Schwarber, 55.5% Vladimir Guerrero Jr., 54.9% Oneil Cruz, 54.9% Gunnar Henderson, 53.9% Ketel Marte, 53.8% Marcell Ozuna, 53.5% Rafael Devers, 52.6%

These 10 names comprised seven of the 10 hitters who hit at least 40 home runs (Judge, Ohtani, Soto, Schwarber, Henderson, Marte and Ozuna), and the group averaged 38 homers. Seven of the 10 finished among the top 12 hitters in either fantasy points scored or on the Player Rater (Judge, Ohtani, Soto, Guerrero, Henderson, Marte and Ozuna).

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

Sal Frelick, 19.5% Steven Kwan, 23.7% Luis Arraez, 23.7% Nolan Schanuel, 25.4% Isaac Paredes, 27.1% Nico Hoerner, 27.6% Andres Gimenez, 28.5% Jacob Young, 28.9% Brice Turang, 29.7% Bryson Stott, 30.8%

Sticking with the 100-inning pitching qualification threshold, here were the 10 best pitchers in terms of Hard Hit Rate in 2024:

Blake Snell, 28.9% Michael King, 30.3% Hunter Brown, 30.3% Nick Martinez, 30.5% Chris Sale, 31.2% Corbin Burnes, 31.6% Michael Wacha, 32.5% Hunter Greene, 32.5% Tyler Anderson, 33.0% Justin Steele, 33.2%

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

Patrick Corbin, 46.7% Logan Webb, 46.2% Yusei Kikuchi, 45.0% Framber Valdez, 45.0% Casey Mize, 44.6% Jared Jones, 44.5% Trevor Rogers, 44.4% Bryse Wilson, 44.3% Jose Soriano, 44.3% Kyle Harrison, 44.1%

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 all 11 who managed at least 60 Barrels in 2024 also hit at least 30 home runs (a level that only 23 hitters reached).

Here were those 11 hitters with 60-plus Barrels, along with their homer totals and ranks:

Aaron Judge, 105 Barrels, 58 home runs (MLB leader) Shohei Ohtani, 103 Barrels, 54 homers (second) Juan Soto, 91 Barrels, 41 homers (fourth) Bobby Witt Jr., 77 Barrels, 32 homers (tied for 16th) Vladimir Guerrero Jr., 72 Barrels, 30 homers (tied for 20th) Marcell Ozuna, 68 Barrels, 39 homers (tied for fifth) Yordan Alvarez, 67 Barrels, 35 homers (11th) Francisco Lindor, 67 Barrels, 33 homers (tied for 14th) Brent Rooker, 62 Barrels, 39 homers (tied for fifth) Teoscar Hernandez, 60 Barrels, 33 homers (tied for 14th) Kyle Schwarber, 60 Barrels, 38 homers (eighth)

To repeat, this is a metric that can also be used to evaluate pitchers. The three ERA qualifiers who allowed the fewest Barrels last season were Hunter Brown (21), Max Fried (24) and Chris Sale (24), while the five who allowed the most were JP Sears (57), Kutter Crawford (52), Kevin Gausman (52), Austin Gomber (52) and Carlos Rodon (52).

Unsurprisingly, Sale posted the majors' best HR/9 ratio (0.46), while Fried ranked sixth (0.67). Crawford (1.67) and Gomber (1.64) had the two worst HR/9 ratios, Rodon was fourth-worst (1.59) and Sears was eighth-worst (1.39). Brown (0.95, 16th among 58 qualifiers) and Gausman (0.99, 17th), however, were middling in the category, illustrating that Barrel rate for pitchers shouldn't be considered a "be all, end all" metric for skills analysis.

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.

Brandon Pfaadt, who took a step forward in some regards in 2024 but still barely cracked the top-50 starting pitchers in terms of fantasy points, had an average Spin Rate of 2,557, fifth-highest among pitchers who threw at least 500 of that specific pitch. Pfaadt's four-seamer averaged only 93.8 mph, below the league average of 94.2, and opponents hit .265 with a .466 slugging percentage against the pitch.

That said, the numbers reflected an improvement in Pfaadt's four-seam fastball metrics, and it was a positive that he decreased its usage to correspond with greater reliance upon his sinker, the two pitches providing a nice contrast to one another. Both pitches improved in performance in 2024, and further reliance upon his secondary offerings -- his sweeper especially -- can only help him moving forward.

Pfaadt's four-seam fastball results do, however, illustrate how neither the Spin Rate metric, nor average velocity on its own, is the solitary indicator of an elite pitch.

Tanner Bibee's cutter, in contrast, gives us an ideal example of a pitch made more effective thanks to its high spin rate. Among pitchers who threw at least 400 cutters in 2024, his had the most average revolutions per minute (2,742). Bibee's cutter was responsible for 50 of his 187 total strikeouts, after notching 51 of his 141 in 2023, and opponents hit just .141 against it with a .205 wOBA.

It's a pitch that has been excellent at helping Bibee minimize hard contact and generate a high rate of pop-ups, his 27.4% hard-hit and 18.0% pop-up rates with the pitch each the game's best rates with a cutter (minimum 400 thrown).

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 2024, along with their finishes among hitters in fantasy points:

Aaron Judge, .479 xwOBA, 630 fantasy points (second) Juan Soto, .462 xwOBA, 582 (fourth) Shohei Ohtani, .442 xwOBA, 653 (first) Yordan Alvarez, .411 xwOBA, 467 (eighth) Vladimir Guerrero Jr., .408 xwOBA, 510 (sixth) Bobby Witt Jr., .407 xwOBA, 590 (fourth) Marcell Ozuna, .402 xwOBA, 436 (tied for 11th) Ketel Marte, .392 xwOBA, 436 (tied for 11th) Corey Seager, .390 xwOBA, 343 (47th) Kyle Schwarber, .380 xwOBA, 406 (tied for 20th)

These categories can also be used to identify regression candidates, players whose batted-ball outcomes were more favorable than they should have been. Tyler Fitzgerald, mentioned in Inning 6 of The Playbook for his unexpected late-season power burst, had the majors' largest wOBA-xwOBA split among hitters with at least 300 plate appearances, 65 points in that direction (.357 wOBA, .292 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 Sprint Speed is usually only a little better than 27 feet per second. Slower runners sometimes see numbers as poor as 22 feet per second, with Yadier Molina, who averaged a worst-in-baseball (among those with at least 50 measured runs) 21.8 feet per second in 2022, a notable recent example.

These were the top 10 performers in Sprint Speed in 2024, among those who had at least 50 "competitive runs" measured, along with their stolen base totals:

Bobby Witt Jr., 30.5 feet/second, 31-of-43 stealing bases Johan Rojas, 30.1 feet/second, 25-of-29 stealing bases Elly De La Cruz, 30.0 feet/second, 67-of-83 stealing bases Tyler Fitzgerald, 30.0 feet/second, 17-of-21 stealing bases Pete Crow-Armstrong, 30.0 feet/second, 27-of-30 stealing bases Victor Scott II, 30.0 feet/second, 5-of-6 stealing bases Jorge Mateo, 29.9 feet/second, 13-of-15 stealing bases Jose Siri, 29.9 feet/second, 14-of-21 stealing bases Garrett Hampson, 29.8 feet/second, 7-of-9 stealing bases Jeremy Pena, 29.8 feet/second, 20-of-26 stealing bases

As you can see, this group went a combined 226-of-283 stealing bases, for an 79.9% success rate that exceeded the league's average (79.0%).

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

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 2024, among those who worked at least 100 innings pitched, all of whom had excellent seasons:

Chris Sale, 2.09 Blake Snell, 2.43 Paul Skenes, 2.44 Tarik Skubal, 2.49 Garrett Crochet, 2.69 Tyler Glasnow, 2.90 Reynaldo Lopez, 2.92 Logan Webb, 2.95 Cole Ragans, 2.99 Cristopher Sanchez, 3.00

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 10 widest ERA-FIP differentials, leaning on the side of their having experienced more misfortune:

Jordan Montgomery, 1.75 run difference (6.23 ERA, 4.48 FIP) Patrick Corbin, 1.20 (5.62, 4.41) Kenta Maeda, 1.12 (6.09, 4.96) Miles Mikolas, 1.11 (5.35, 4.24) Brandon Pfaadt, 1.10 (4.71, 3.61) Kyle Hendricks, 0.94 (5.92, 4.98) Garrett Crochet, 0.89 (3.58, 2.69) Nick Lodolo, 0.81 (4.76, 3.95) Jon Gray, 0.77 (4.47, 3.70) Sonny Gray, 0.72 (3.84, 3.12)

That's not to say that Hendricks is destined for a major rebound in 2025, especially since a 4.98 FIP is anything but a pretty number. But in his, and the rest of the list's, defense, several of the names on last year's top-10 list -- Brady Singer, Dylan Cease, Luke Weaver, Taj Bradley and Hunter Brown -- enjoyed substantial improvements in fantasy value in 2024.

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

Michael Lorenzen, minus-1.58 run difference (3.31 ERA, 4.89 FIP) Ronel Blanco, minus-1.35 (2.80, 4.15) Andrew Abbott, minus-1.33 (3.72, 5.04) Jose Berrios, minus-1.11 (3.60, 4.72) Bowden Francis, minus-1.06 (3.30, 4.36) Bryse Wilson, minus-1.05 (4.04, 5.09) Luis L. Ortiz, minus-0.93 (3.32, 4.25) Reynaldo Lopez, minus-0.93 (1.99, 2.92) Tobias Myers, minus-0.91 (3.00, 3.91) Javier Assad, minus-0.90 (3.73, 4.64)

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 2024, using the 100-inning threshold for qualification:

Chris Sale, 2.80 Tarik Skubal, 2.89 Sonny Gray, 3.03 Jack Flaherty, 3.10 Logan Gilbert, 3.19 Yusei Kikuchi, 3.30 Zack Wheeler, 3.32 Framber Valdez, 3.41 Pablo Lopez, 3.46 Dylan Cease, 3.46

'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. Strangely enough, after the league's BABIP ranged between .290-.292 from 2020-22, it rose to .297 with new rules in place governing shifts in 2023, then returned to .291 under those same new rules last season.

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 2024, the top qualified hitter in terms of BABIP was Seiya Suzuki (.370), and his number was 34 points higher than his career rate in the category entering the season and 29 points higher than his 2023 mark. That comparison hints that some batting average regression should be anticipated with him in 2024.

It's fair to point out, however, that Suzuki's .347 career BABIP through three years in the States ranks seventh-best among players with at least 1,000 plate appearances, and he also had a .329 BABIP during his career in Japan. Don't expect 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 above, Home Run per Fly Ball Percentage determines how fortunate a player might have been with fly balls he hit clearing the outfield fence for a home run. The league's annual average in the category varies more than does BABIP, but in 2024 was 9.9% -- and that comes on the heels of a 9.7% rate in 2022 and 10.6% in 2023. 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 2024, Framber Valdez (13.4%) had the highest qualified rate among pitchers, while Sonny Gray, who finished 21st among starting pitchers and 50th overall in fantasy points, had a 13.2% rate after posting the league's best number in the category in 2023. Chris Sale had the majors' lowest rate in 2024 (6.3%).

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 slighty differences in formulas. For example, FanGraphs had the league's average Home Run per Fly Ball Percentage as 11.6%.

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 2024 it was 72.1%. Last season among ERA-qualified pitchers, Ronel Blanco was the leader in the category (83.6%), while Miles Mikolas (62.9%) brought up the rear. Blanco's Strand Rate was easily the best he had ever posted at any stop in his nine-year professional career, heightening concerns that he'll regress in 2025.

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, Daulton Varsho had the majors' highest pop-up rate among batting title-eligible hitters, having popped the ball up 18.2% of the time that he put it into play. FanGraphs includes these in his fly-ball rate, which is how he had a 52.9% number there, second-highest among 129 qualifiers, whereas he had a mere 30.6% fly-ball rate per our internal pitch-tracking tool, 32nd-highest among that same group. Those looking at Varsho's fly-ball rate on FanGraphs might assume he'll be more capable of clearing the Rogers Centre's higher outfield fences -- they raised the heights before the 2023 season -- than he actually is.

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

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, Aaron Judge (.499) occupies the top spot using this split, while Dominic Fletcher (.185) ranks last.

Michael Harris II's strong finish -- he hit .316/.344/.579 with eight home runs and 18 RBI in 26 September games, his wOBA a sixth-best .431 using the above link -- is probably one of the reasons many fantasy managers are so bullish on drafting him entering this season.

FanGraphs is another site that offers custom statistics reports, including those you can download. Here is where you can find the basic 2024 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 2024 away-games split. There, you'll see that Cristopher Sanchez had a 5.02 ERA in his 14 starts away from Philadelphia's Citizens Bank Park, giving him a near three-run differential between his home (2.21) and road ERAs, the second-widest among qualifiers in that direction.

As a quick note, as FanGraphs isn't a paywalled 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.