Hello Friends! Our regression group continues to grow as we identify more low strikeout pitchers outperforming their skilled-based metrics or guys who have just been plain unlucky. Hopefully, by now, you have a good understanding of the key characteristics an ideally above average pitcher will display compared to a potentially fluky one. Let’s dig into this week’s candidates!
The Tigers’ left-hander has only been in the rotation for three starts in 2019 so let’s utilize previous seasons’ data as a way to build a bigger sample size for his assessment.
Over 29 starts since 2017, Norris has produced an average 9.3% swinging strike rate and an ugly 4.64 Skilled Earned Run Average (SIERA) which gives us reasons to be skeptical of his current 3.47 Earned Run Average (ERA). Combined with his overall large amount of hard contact allowed (41.3%), lofty fly ball percentage (39.9%), and a generous number of home runs allowed (24 in 169.1 innings), a spike in this 26-year old starter’s ERA seems inevitable.
Further signs of trouble can also be found when looking into other peripherals. Through 23.1 innings this season, Norris’ Left On Base Percentage (LOB) is at 88.4% despite a Batting Average on Balls in Play (.351) larger than his career number (.315).
It’s only a matter of time before some team destroys this Detroit pitcher, especially with runners on base. Cash in on all this future regression by using Angels’ hitters in his next start on Tuesday!
Like Norris, we are somewhat dealing with smaller data sample sizes, but we should still expect this Rangers’ pitcher to eventually regress in 2019.
The first sign of concern can be seen through Sampson’s skill-set. Over a 55.1 innings sample size since 2016, the 27-year old is only averaging 5.86 K/9, resulting in a career 4.80 SIERA. When narrowed down to this current season, Sampson has already allowed 20 hits in his three starts (15.0 innings), which means he is constantly pitching with runners on base. It is not crazy to assume opposing teams will eventually be scoring a bunch of runs off him, especially since his stuff is not known to be overwhelming (career 8.3% swinging strike rate).
Future regression can also be found when examining his batted ball statistics. Through eight career starts, Sampson’s hard-hit and fly ball percentages stand at 40.0% and 40.4% respectively which is not good news for a pitcher who calls Globe Life Park his home (our highest ranked hitting environment).
It would be in your best interest to avoid this pitcher at ALL costs!
After allowing 21 earned runs in 36 innings pitched, most of the public is very down on this high profile left-hander, but we should feel confident Sale can turn it around soon.
The first sign of future positive regression can be seen through his strikeout metrics. Despite the slow start, Sale’s 12.1% swinging strike rate is actually on par with his career percentage (12.8%) and his 3.71 SIERA gives us a better indication his stuff is still working. When considering his overall strikeout production (42 strikeouts in seven starts), his slight dip in fastball velocity (from 95.7 to 93.0) should be the only reason we remain concerned.
Negative recency bias can also be considered a bit premature when examining this lefty’s batted ball profile. For his career, Sale’s LOB Percentage stands at 78.1% which allows us to treat his current 67.2% as a data outlier. Yes, his 32.8% hard-hit rate is a little concerning compared to his career 27.6% mark but his line drive, fly ball, and ground ball percentages still remain stabilized.
Is Sale no longer the dominant ace we have grown accustomed to? Maybe, especially if he can’t regain full strength with his fastball but we should still treat this veteran as an above average starter. Take advantage of his current perception and buy low on his stock especially in daily fantasy!
As usual, don’t be afraid to holla @ me on Twitter or any of our staff in the chat if you have any questions. Our MLB product continues to pump out new ways to gain an edge on your competition including our Bullpen Factors Tool, which provides information about a bullpen’s usage and performance. Take advantage of all the unique applications The Quant Edge has to offer and continue pumping out those green screens!
Matt is an avid all around sports fan that somehow managed to pick the unlikely combination of the Mets and Eagles as his two favorite teams. After graduating from Rutgers University in 2011, Matt learned of DFS from a few poker friends of his and soon became intrigued with GPPs and the opportunity to create unique teams in several different sports. During his free time, Matt can be seen watching the Mets blow late leads, pigging out on cookies and pizza, napping, and searching for underrated diners.