This space has frequently made use of luck in explaining the largest gaps between player results and xStats. It must be noted though that luck alone does not encompass those statistical discrepancies. For example, fielder positioning/shifting will influence the relationship between actual and expected statistics in ways that are not strictly luck based, especially since xStats do not account for directionality of balls in play. A hitter that routinely smokes line drives into the shift will underperform his xBA despite the high quality of contact as more of those liners will become outs.
This series focuses on notable outliers with the largest xStat discrepancies because luck plays a greater role in explaining the biggest gaps, and therefore those particular players are the most likely to experience regression in an obvious direction. This can help us in fantasy to make trades or adds/drops that maximize the total output we get from a single roster spot. It’s easier to spot the sell high and buy low players using xStats as a tool, but we must always remember that xStats are not predictive and that the underlying skillset is still the most important factor.
Last week we highlighted three SP whose numbers have been held down by the fickle hands of fate. This week flips the script and shines the spotlight on four pitchers who have benefitted the most thus far from well-struck batted balls turning into well-struck batted outs.
All xStats via Baseball Savant thru 6/21
xStat Overachievers: Pitchers
Logan Gilbert – SEA
Logan Gilbert was expected to see improvement from his rookie season last year, when his 4.68 ERA belied strong underlying skills. So far this year, Gilbert’s 2.28 ERA and 1.04 WHIP appear to have vaulted him into the fantasy ace tier earlier than even the most optimistic projections expected. The xStats tell another story though; that his numbers should fall somewhere in between the results of 2021 and 2022.
This is fully supported by a deeper look at Gilbert’s metrics. His average EV (91.5 mph) and hard hit rate (48.2%) are both in the lowly 5th percentile amongst qualified pitchers. Those are far from ace-like numbers, and Gilbert has been fortunate that much hard contact has amounted to so few hits and runs scored. Gilbert has also allowed a mere 6.9% HR/FB ratio, 12th lowest out of 61 qualified starters, despite his fly ball rate of 39.4%, which is the 20th highest out of those 61 qualifiers. That much hard contact in the air could lead to more homers down the road.
None of this makes Gilbert an automatic sell-high in trade, but it’s likely he’s already had the best stretch of his 2022 season. Dynasty and keeper leaguers have a tremendous long-term asset, but those in single-season leagues may need to consider that Gilbert won’t be carrying their ratios deep into September. As he approaches a new professional high in IP later this year, fatigue could impact his performance in addition to an expected shift in batted ball fortune. Combine that with a possible early hook due to innings limits and those in H2H leagues with playoffs may not have Gilbert at his best when they’d need him the most.
Jordan Montgomery – NYY
Jordan Montgomery looked like a future MLB SP3 as he made his way up the minor league levels, and his 2017 rookie season fit that description perfectly: 3.88 ERA, 1.23 WHIP, 8.34 K/9. Everything good but nothing great. He was denied the opportunity for a follow-up due to Tommy John surgery early in his sophomore campaign which limited him to just 31.1 IP between ’18-’19. It wasn’t until last year when Montgomery again had the chance to show his stuff for a full season. The result was a near carbon copy of his 2017 rookie year. Jordan Montgomery was “back”, even if that only meant as a useful SP3.
This year’s surface stats look like a Jordan Montgomery breakout based on his elite 2.72 ERA and 0.95 WHIP, but under the hood he’s only been a slightly better version of himself in some areas, while regressing in others. xStats agree, indicating he’s basically the same pitcher this year that he was last year and at the beginning of his career. The most notable improvement has been his incredible 3.8% walk rate (MLB average is 8.4%). That level of control is a nice safety net for his WHIP. The drop in walk rate was accompanied by a larger drop in K rate though, from 24.5% last year to a below-average 19.4% rate in 2022. This has been especially harmful in points leagues that favor K’s.
Montgomery succeeds in limiting hard contact, a skill which has continued in 2022 (5.6% barrel rate, 34.4% hard hit). Hard contact suppression and a strong ground ball rate will continue to give Montgomery a safe floor of fantasy value, but the lack of strikeouts will only exacerbate his rise in ratios should his career-best BABIP (.245) and strand rate (81.3%) regress towards his career marks. Montgomery is a perfectly cromulent fantasy pitcher, he’s just not a sub-3.00 ERA, sub-1.00 WHIP ace like his numbers currently suggest. He’s a fine piece of a roto rotation, but if points-leaguers can turn the fantastic-looking ratios into a high-K starter with upside like Robbie Ray, now may be the best time.
Michael Wacha – BOS
Michael Wacha was on some fantasy radars during 2022 draft season after a late season pitch mix in 2021 lead to a spike in K rate and a strong finish. Signing in Boston and the AL East quieted the high hopes, but those who took a late-round gamble anyway (or were early on waivers) have been well-rewarded so far. Wacha’s 2.27 ERA and 1.03 WHIP are both career bests and he has managed 5 wins while backed by Boston’s strong offense, despite reaching 5 IP only seven times in 11 starts.
When we look deeper at Wacha though, we actually see a profile similar to that of Jordan Montgomery, but without the help of a high ground ball rate and elite walk rate to soften the blow should regression inevitably come calling. Wacha limits hard contact well, posting a 5.7% barrel rate and 33% hard hit rate but his BABIP (.224) and strand rate (84%) have been even more fortunate than Montgomery’s.
Unfortunately, the increase in K rate that Wacha produced to end 2021 has not carried over into 2022. In fact, his K rate has plummeted to just 17.4%, even lower than Montgomery’s below-average rate. When a pitcher allows as much contact as Wacha does, he’s naturally more dependent on batted ball luck to sustain excellent ratios, and Wacha’s overall profile suggests that luck has played an outsized role in his accomplishments so far. He’s an excellent sell-high candidate since regression could hurt him far more than Montgomery or Gilbert. For those in leagues without trading, ride the hot streak while it lasts but don’t be afraid to cut Wacha loose once those ratios start climbing back up.
Gregory Soto – DET
Gregory Soto becomes the first closer to make an appearance on xStats Weekly, but for all the wrong reasons. On the surface, he appears to be doing a fine job as the Tigers’ closer with a 2.88 ERA and on pace for 30+ saves, but the sheer number of red flags in Soto’s underlying metrics are eye-catching, and the xStats reflect this.
Soto sports a weak 22.6% K rate combined with a bad 11.3% walk rate. He is allowing a ton of hard contact (93.5 mph avg EV, 9.2% barrel rate, 46.2% hard hit rate!) yet has a ridiculously low 3.3% HR/FB ratio. His flyball rate is high and his chase rate is low. The only real positive for Soto is that his zone contact rate is better than league average, but he offsets this by his inability to consistently hit the zone. This is the profile of a journeyman reliever, not a reliable fantasy closer.
For some reason, A.J. Hinch seems to prefer Soto in the closer role and has given him a long leash. It’s hard to imagine Soto holds much value outside of roto leagues or those that weight saves heavily, but even then he’ll only be useful for as long as he can continue the smoke and mirror show. It’s likely Soto will lose his job at some point, and all fantasy relevance along with it. Michael Fulmer has been the superior reliever and Hinch may eventually be forced to give him the primary closer role.
Photos by Icon Sportswire | Adapted by Justin Paradis (@JustParaDesigns on Twitter)