MLB League Trends & Impact on Fantasy Baseball Player Values (2024)

MLB League Trends & Impact on Fantasy Baseball Player Values (2024)

Standard fantasy categories may be considered outdated to some. However, the majority of leagues still play using the standard 10 categories of BA, R, HR, RBI and SB offensively and then for pitching W, K, S, ERA and WHIP.

There are always trends in fantasy baseball where some categories or stats outpace others in scarcity, and 2023 was no different. We had new rules that increased SB output, others that increased the number of platoon bats and many that affected how deep pitchers were going and their overall effectiveness. Follow below as I detail the trends in each category and how they might impact the values of specific players entering 2024.

As we go, we will be using my fScores as a guide for specific categories. If you are curious about the fScore ratings, you can check out my fScore rankings and information on the fScores here and find me on Twitter/X @fantasyaceball.

League Trends & Impact on Player Values

Batting Average (AVG/BA)

Batting average has been on a steady decline for decades now, and the trend is not yet reversing, though it might have hit rock bottom.

Season AVG OBP BB% K%
2000 0.270464462 0.344916071 0.095852539 0.164805188
2001 0.263959238 0.332202164 0.084534913 0.173305664
2002 0.261331175 0.331203304 0.087056238 0.168228706
2003 0.264230494 0.332569115 0.084764389 0.164316694
2004 0.266036461 0.33510718 0.086040553 0.168813879
2005 0.264475131 0.330322329 0.081629037 0.164492683
2006 0.269348217 0.336570082 0.084260731 0.168314094
2007 0.26806649 0.335783553 0.085244111 0.170652571
2008 0.263757092 0.333073599 0.087069833 0.175258885
2009 0.262431488 0.332932452 0.088839474 0.179555161
2010 0.257352452 0.325473826 0.085032308 0.184885181
2011 0.255073775 0.320559408 0.081071014 0.186175065
2012 0.254540063 0.318956409 0.079862525 0.19777499
2013 0.253465406 0.317602812 0.079189926 0.198569821
2014 0.251156303 0.313683495 0.076225479 0.20356335
2015 0.254435366 0.316790482 0.076639056 0.203924259
2016 0.255349991 0.321583094 0.081743662 0.211196411
2017 0.254972307 0.324461419 0.085425942 0.216433255
2018 0.247944774 0.318144078 0.08472553 0.222573309
2019 0.252257712 0.322694959 0.08522057 0.229594243
2020 0.244604438 0.321832843 0.091600757 0.234354795
2021 0.243817192 0.317089341 0.086867564 0.231799006
2022 0.242712507 0.311551424 0.081586579 0.224177707
2023 0.248385213 0.320134655 0.08592426 0.227279146

The chart above shows us that batting average dipped steadily from .270 down to .242 in 2022 but then bounced back up to .248 in 2023. This may be an outlier, or it may be showing us that 2022 was the rock bottom of “three true outcomes,” and the rule changes are starting to bring the game back to “normal.”

One interesting thing is that when considering “three true outcomes,” there is a direct correlation between more strikeouts and worse batting average. Still, OBP pretty much follows the decrease in batting average because BB% has more or less maintained stability through the last 20-plus seasons.

Between the changes in the shift rules and the pitch clock, we are seeing batting average bounce back, and K% might have hit a peak as it’s been stabilized since around 2018. Generally, the players we should see continue to benefit most due to the rule changes in the batting average category are high-contact hitters that avoid strikeouts with at least moderate speed, as the correlation between league-wide batting average with hard-hit rate and barrel rate is non-existent.

Bounce-back/Breakout Candidates (.270+ batting average):

Runs (R)

There are up seasons and down seasons, but since 2001, the average number of runs scored is about 22,000 in total, so there is really nothing trending here. Even with the new rules in 2023, the number of runs was 22,432.

There are a few key factors that contribute to run scoring:

  1. Lineup Spot (top four in the lineup)
  2. Quality Lineup
  3. On-base Skills

There’s a myth that speed plays into the number of runs scored, which helps a little, but players like Freddie Freeman, Matt Olson, Austin Riley and Kyle Schwarber all finished in the top 10 of players in runs scored in 2023. So, let’s break down these three factors…

A total of 34 players scored 90+ runs in 2023.

  • All 34 players hit in the top four spots in their lineup, and 30/34 hit in the top 3, with the exceptions being Pete Alonso, Kyle Tucker, Matt Olson and Max Muncy.
  • Team Breakdowns (w/ more than 1 90+ run scorer):
    • Braves: 4 (3 w/ 100 runs)
    • Dodgers: 3 (2 w/ 100 runs)
    • Rangers: 2 (2 w/ 100 runs)
    • Diamondbacks: 2 (1 w/ 100 runs)
    • Mets: 2 (1 w/ 100 runs)
    • Phillies: 2 (2 w/ 100 runs)
    • Astros: 2 (1 w/ 100 runs)
    • Mariners: 2 (1 w/ 100 runs)
    • Cubs: 2
    • Rays: 2
    • Padres: 2
  • On-base Skills: The average OBP of the 90+ run players is .356 vs. .320 league-wide OBP.

Bounce-back/Breakout Candidates (90+ runs):

Home Runs (HR)

Homers averaged around 5,300 from 2000-2006, then saw a huge downtick (likely due to performance-enhancing drug crackdown) from 2007-2015 to about 4,800. 2016 must have seen a real enhancement in bouncy balls (even though 2019 is the known super ball year), as homers ticked back up since then to 5,800-6,000 per year, way more than even the steroid era. I would attribute this to the balls and the launch angle revolution and the start of the “three true outcomes” era. Still, homers have been pretty stable for close to 10 years at this point.

When looking for potential breakouts, we want to find players who hit the ball hard and just need an adjustment in launch angle or adjustment that leads to more barrels, therefore smashing more homers. So, looking at potential homers, let’s look at some players who hit the ball really hard but aren’t necessarily home run hitters.

Bounce-back/Breakout Candidates (25+ home runs):

Runs Batted In (RBI)

RBI is similar to the premise of runs, where there are a few big contributing factors.

  1. Lineup Spot (hitting in the 2-5 spot)
  2. Quality Lineup
  3. Over .200 ISO

A total of 35 players scored 90+ RBI in 2023.

Bounce-back/Breakout Candidates (90+ RBI):

FantasyPros Fantasy Baseball Draft Wizard

Stolen Bases (SB)

While the new rules didn’t seem to affect the other categories so much, stolen bases had a definite effect, with a 41% jump in stolen bases y/o/y from 2022 to 2023 (with only a 7% increase in caught stealing). In 2023, there were a total of 3,503 stolen bases, the most steals since 1987 (3,585 total steals) and the second most steals since 1915. Additionally, there was a major increase in stolen base efficiency (80.2% success rate), whereas in 1987 – the highest steals total since 1915 – the success rate was only 70.1%, so we could see an even bigger uptick in steals in 2024.

Stolen Bases depend on a few different items.

  1. Lineup Spot / Opportunity (top 1/3 of lineup)
  2. Team Context
  3. Speed & Baserunning Skills (including the desire to steal)

A total of 31 players had more than 20 steals in 2023

  • 24/31 players hit in leadoff, second or third
  • 3 teams attempted at least 200 SB:
    • Reds
    • Royals
    • Rays
  • 13 teams attempted at least 150 SB:
    • Diamondbacks
    • Guardians
    • A’s
    • Phillies
    • Cubs
    • Padres
    • Braves
    • Brewers
    • Nationals
    • Pirates
  • 2 teams attempted less than 100 SB:
    • Rangers
    • Giants
  • Much of this is obviously player-dependent, but we also see the Rays again leading the league in trends.

Bounce-back/Breakout Candidates (20+ steals):

Pitcher Wins (W)

I hate this stat, to be quite honest. Unless I’m playing in an “industry” or NFBC league, I’m avoiding wins and leaning toward leagues that focus on IP or QS rather than wins as a category or points structure. There is obviously nothing trending or changing in wins, and most of the time, this stat can be random. For example, Matt Brash had nine wins last year as a late-inning reliever.

What can you do to get as many wins as possible?

Well, simply draft pitchers who tend to log quality starts on really good teams. Reliever wins are more or less based on luck, and you can’t predict them except for just rostering relievers on the best teams.

Teams projected for 85+ wins by PECOTA in 2024:

  1. Los Angeles Dodgers (101)
  2. Atlanta Braves (100)
  3. Houston Astros (95)
  4. New York Yankees (94)
  5. Toronto Blue Jays (88)
  6. Minnesota Twins (88)
  7. Baltimore Orioles (87)
  8. Tampa Rays (86)
  9. Texas Rangers (86)
  10. Seattle Mariners (85)
  11. St. Louis Cardinals (85)
  12. Arizona Diamondbacks (85)

Bounce-back/Breakout Candidates (15+ wins):

Strikeouts (Ks/SOs)

As noted above in the chart, batting average is down, and a direct correlation of that is strikeouts being up. Strikeouts averaged around 31,000 from 2000-2007, then starting in 2008, there was a steady rise y/o/y from 32,000 to 38,000 in 2016. In 2017, strikeouts jumped to 40,000 and have averaged close to 42,000 from 2017-2023. There hasn’t been a rise in strikeouts during this period, and we seem to have hit a plateau, so there isn’t much of a trend to watch.

Quite simply, Ks are all about stuff and durability combined, thus we will use fStuff and fDurability as a basis for who will jump up in Ks in 2024.

There were 17 total starters with 200+ strikeouts in 2023 (only one had more than 250: Spencer Strider), while 27 total starters had more than 180 strikeouts in 2023.

Bounce-back/Breakout Candidates (180+ Ks):

Saves (S)

With saves, you want to have a similar strategy as you do with wins:  Pick the closers for the best teams that are least likely to blow saves (best at run prevention). This is more important than closers who rack up Ks for the purpose of saves (see Emmanuel Clase). You also want to pick closers who are “locked-in” to the role rather than those who might be in time-share situations.

Locked-In Closers:

  1. Edwin Diaz
  2. Emmanuel Clase
  3. Devin Williams
  4. Pete Fairbanks
  5. Andres Munoz
  6. Jhoan Duran
  7. Ryan Helsley
  8. David Bednar
  9. Clay Holmes
  10. Raisel Iglesias
  11. Camilo Doval
  12. Jordan Romano
  13. Paul Sewald
  14. Alexis Diaz
  15. Kenley Jansen (when healthy)
  16. Adbert Alzolay
  17. Justin Lawrence

Closer Questionable:

  1. Josh Hader / Ryan Pressly
  2. Tanner Scott / AJ Puk / Andrew Nardi
  3. Evan Phillips
  4. Craig Kimbrel / Yainer Diaz
  5. Mason Miller / Lucas Erceg / Dany Jimenez
  6. Jose Alvarado / Orion Kerkering / Jeff Hoffman
  7. Jose Leclerc / David Robertson
  8. Alex Lange / Jason Foley / Shelby Miller
  9. Carlos Estevez / Robert Stephenson
  10. Will Smith / James McArthur
  11. Kyle Finnegan / Hunter Harvey

Up In the Air:

  1. Yuki Matsui / Robert Stephenson / Woo-Suk Go
  2. John Brebbia / Prelander Berroa

Earned Run Average (ERA)

ERA, in general, is a pretty stagnant statistic, averaging 4.25 since 2000 and 4.19 over the last 10 seasons.

The best way to help ERA is to find players who pitch a ton of innings and prevent the most runs, DUH. There are better predictive ERA metrics than ERA itself, such as fERA and SIERA. For this exercise, we will look at players with an ERA over 3.50 that should be under 3.50 in 2024.

Bounce-back/Breakout Candidates (under 3.50 ERA):

Bounce-back/Breakout Candidates (under 4.00 ERA, who were over in 2023 or rookies):

Walks + Hits/Innings Pitched (WHIP)

WHIP, as a statistic, actually decreased pretty significantly after 2009, which is likely in part due to massive shifting starting to occur and an increase in defensive analytics. From 2000-2009, the league average WHIP was 1.40. Since 2010, the league average WHIP has hovered around 1.31, with the 2023 season nailing that exact figure. So, I would say there is no trending difference in WHIP y/o/y at this point.

WHIP is a matter of control and limiting damage at the same time. When looking for a good WHIP, we want to find players who will run under a 1.20 WHIP on the elite ends of pitching and definitely under a 1.30 WHIP, even with the deepest starters. Using fControl, here is a list of pitchers who rate highly while still racking up a higher than 1.20 WHIP on the 2023 season.

Bounce-back/Breakout Candidates (under 1.20 WHIP):


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About Author

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Tim Kanak

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I have a Broadcast Journalism degree from the University of Missouri and reported sporting news for the local NBC affiliate. I also have a Masters from UCF. I own and operate multiple construction businesses in South Florida and in my free time write about fantasy baseball and podcast; including creating the fScores. Find me via the Fantasy Aceball Podcast, here on Fantasy Pros or on FWFB. Twitter @fantasyaceball.

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