Regression is often a hard thing to predict correctly. Much of a player’s performance in fantasy baseball is due to luck, external factors, team environment and opposing pitchers. There is only so much a player can do to improve performance when they have four plate appearances a game or 100 pitches in a week.
Last week, this column correctly predicted a positive regression for Corbin Carroll (.286/.375/.762 with two home runs this week) and a negative regression for Willy Adames (the 181st-ranked fantasy baseball hitter over the last seven days). However, Tyler Anderson continued to roll, defying expectations for negative regression.
This series highlights players due for positive or negative regression compared to their recent performance each week to assist fantasy managers in viewing each one properly. Digging underneath the surface stats, we will examine some hitting and pitching metrics to try to determine if a given player is overperforming or underperforming what should be expected.
With the MLB Trade Deadline now upon us, the goal here is to identify players who are due for hot streaks and cold streaks and acquire them before the value rises or sell high before the crash. Below are four players worth considering.
Regression is often a hard thing to predict correctly. Much of a player’s performance in fantasy baseball is due to luck, external factors, team environment and opposing pitchers. There is only so much a player can do to improve performance when they have four plate appearances a game or 100 pitches in a week.
Last week, this column correctly predicted a positive regression for Corbin Carroll (.286/.375/.762 with two home runs this week) and a negative regression for Willy Adames (the 181st-ranked fantasy baseball hitter over the last seven days). However, Tyler Anderson continued to roll, defying expectations for negative regression.
This series highlights players due for positive or negative regression compared to their recent performance each week to assist fantasy managers in viewing each one properly. Digging underneath the surface stats, we will examine some hitting and pitching metrics to try to determine if a given player is overperforming or underperforming what should be expected.
With the MLB Trade Deadline now upon us, the goal here is to identify players who are due for hot streaks and cold streaks and acquire them before the value rises or sell high before the crash. Below are four players worth considering.
Fantasy Baseball Regression Candidates
(Stats up to date through July 29)
Players Due for Positive Regression
George Springer (OF – TOR)
On May 18, George Springer got a huge batting order demotion. A leadoff man since 2015, Springer was dropped to sixth in the order for the first time in many years. This was a direct result of Springer hitting .198/.270/.287 with just three home runs up to that date. That move must have lit a fire under him because he has been much better since then, even regaining his leadoff role a month later.
Since then, Springer is hitting .251/342/.454 with 10 home runs and six stolen bases. He has raised his batting average by 30 points in that span, but the underlying data show that there still may be more improvement to come for Springer as the last two months of the season arrive.
Springer has one of the 10 largest discrepancies between his batting average (.228) and his expected batting average (.263), according to Statcast. Among hitters with at least 400 plate appearances, Springer trails only Christopher Morel in that category. The gap has been closing since late May, but there is still much room for improvement for the veteran outfielder. He has shown it in July with a .273/.340/.511 line in his 23 games.
Gerrit Cole (SP – NYY)
The New York Yankees have certainly been active at the trade deadline. They traded for Jazz Chisholm, are rumored to be in the mix for Jack Flaherty and activated Giancarlo Stanton from the IL on Monday. But the biggest deadline news the Yankees could make is when Gerrit Cole starts turning his season around. That’s something that is likely to happen sooner rather than later.
Since his July return from injury, it has been far from a typical Cole performance in his first seven starts. He has a bloated 5.40 ERA and is walking a career-high 3.09 men per nine innings, giving up 2.8 home runs per nine. Cole is also striking out under 10 men for every nine innings pitched. His ground ball rate is a career-low, and he is allowing the highest barrel rate to batters of his career (10.7%).
However, Cole’s .376 wOBA allowed is 36 points higher than his expected wOBA (xwOBA), which is the 15th-largest discrepancy among pitchers with at least 100 balls in hit in play, according to Statcast. That data shows his ERA should be around 4.60 and not 5.40, while his slugging allowed should be .464 instead of .525. With only seven starts under his belt, Cole is really in the early stages of his season ramp-up and should be much better going forward.
Players Due for Negative Regression
Tyler O’Neill (OF, DH – BOS)
Naming Tyler O’Neill as a player who is likely to regress negatively the rest of the season brings me personal pain because I am extremely overexposed across my fantasy teams. O’Neill has been a power explosion this year with 22 home runs in just 77 games (a 46-home-run pace over a whole season). Despite missing 25 games, he might pass his career-high of 34 home runs in 2021. O’Neill’s .554 slugging percentage this year is the second-highest of his career and is 80 points more than his career average.
Certainly O’Neill’s park factors into his power surge this year. Fenway Park ranks second in Park Factor runs over the last three years, but there is also some flukiness in O’Neill’s power. His slugging percentage is more than 50 points higher than his expected slugging (.499). Of course, .499 is an exceptional number, but it just speaks to the fact that the power might be coming down a bit in the last two months.
Perhaps the primary reason for the inflated slugging is just the sheer luck on fly balls. In the second half, 40% of O’Neill’s flyballs have gone for home runs. That’s a crazy, unsustainable number that is 38 percentage points higher than the league average. O’Neill has enough raw power to hit another 10 dingers this year, but that 40% number won’t last much longer.
Josh Smith (3B – TEX)
Sometimes, regression can be as simple as a lack of opportunity or playing time. With Josh Jung activated from the IL yesterday after a months-long wrist injury, Josh Smith’s time in the Rangers’ lineup might start to significantly shrink. However, even if Texas does find some way to keep him in the lineup five out of every seven days as a type of super-utility player, Smith has seen some gaudy stats that don’t line up with the expected production.
Smith, who hit .190/.304/.328 last year over 232 plate appearances for Texas, is scorching all those numbers this year. Across 100 games in 2024, Smith is hitting .284/.382/.453 with 11 home runs and seven steals. But based on his batting average on balls in play (BABIP) and his decreased barrel numbers, those totals look to come down soon.
Smith’s .340 BABIP is one of the 20-highest numbers in the league, around players like Rafael Devers and Steven Kwan, both elite contact hitters who have more plate discipline than Smith. In addition, Smith’s barrel rate of 10.5% in 2023 has tumbled down to just 3.5% this year, and his hard-hit rate is down two percentage points as well. I would sell high on Smith if I can because he is about to get hit with the double tap of reduced playing time and regression to the mean.
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