We finally reach the point of the season where we are able—probably—to look back upon the last game to be snowed out…until the playoffs. Hard to believe it, but there are only TWO MONTHS left in the NHL and NBA seasons. #seriously. Remember when these were winter sports?

Today, I offer a brief, broad overview of how March/April stats stack up in comparison to the entire season and then have a look at some of the SP who appear to be studs and duds. Keep in mind that March/April stats are likely to have a lot of white noise associated with them. The weather can be crummy, even the best of SP may need some time to get back into rhythm, rising stars may fizzle and find their way back to the minors, and rookies who do not realize they are in the bigs may still be throwing like gods until they wake up. Rotations are in flux. (That’s especially true this year with teams messing around with larger rotations). Finally, the increasing role of middle relievers and decreasing number of IP thrown by SP will have an impact on the data.

Nonetheless, if we assume that seasons generally follow similar patterns, we can make some broad analyses…

Season Trends

To get perspective on the usual stats I look at, the next two tables offer season-long and March/April splits for the last 5 years.

League Season Stats–SP

Year K/9 BB/9 BABIP HR/FB ERA PIP PBF LD% GB% FB% SwK% 2014 7.36 2.69 0.296 9.80% 3.82 16.0 3.8 20.90% 44.60% 34.50% 8.90% 2015 7.40 2.72 0.297 11.60% 4.10 16.0 3.8 21.10% 45.20% 33.70% 9.30% 2016 7.75 2.96 0.298 13.30% 4.34 16.4 3.8 20.90% 44.30% 34.80% 9.50% 2017 7.96 3.13 0.299 14.20% 4.49 16.6 3.9 20.70% 44.00% 35.30% 9.80%

League March/April 2018 Stats–SP

Year K/9 BB/9 BABIP HR/FB ERA PIP PBF LD% GB% FB% SwK% 2014 7.64 2.87 0.296 10.20% 3.88 16.2 3.8 20.00% 45.80% 34.20% 9.10% 2015 7.28 2.83 0.297 11.00% 4.15 16.0 3.8 21.30% 45.70% 33.10% 8.70% 2016 7.89 3.20 0.297 11.80% 4.10 16.5 3.9 21.00% 45.10% 33.90% 9.40% 2017 7.88 3.13 0.288 13.00% 4.04 16.2 3.8 20.20% 44.40% 35.40% 9.80% 2018 8.39 3.29 0.287 12.60% 4.20 16.6 3.9 20.70% 43.30% 36.00% 10.10%

One remarkable thing to take away from this data is that the league settles into its season-long trends pretty quickly. The March/April splits are pretty close to the season averages. Keeping this in mind, let’s take a look at league averages thus far and break them down a bit. For March/April 2018, the averages and standard deviations of the key indicators for SP (as defined by Fangraphs) are:

March/April 2018 Individual SP Data

IP K/9 BB/9 BABIP HR/FB ERA PIP PBF LD% GB% FB% SwK% average 23.4 8.2 3.56 0.296 0.140 4.92 17.4 3.91 21.3% 42.8% 35.9% 9.8% stdev 10.7 2.4 1.8 0.07 0.1 3.55 2.59 0.29 7.1% 10.0% 8.4% 2.9%

Some things to keep in mind. First, to make more accurate assessments of individual SP, it is very helpful if the data tend to be bell-shaped. If so, then we can make quick, straightforward comparisons using the league average and standard deviation. If the data are not bell-shaped, we need to use other measures. In those cases, I’ll look at the distributions in terms of quarters—who is in the top 25%, etc. In the following Data, I remove the following pitchers:

Parker Bridwell Angels Brandon Woodruff Brewers Jason Vargas Mets Eric Lauer Padres Cody Reed Reds

Words can’t describe just how heinously bad these guys were or have been this year. In some cases (Bridwell), they didn’t get out of the one inning they pitched. In Bridwell’s case, he threw 36 pitches and left. These guys all occupy the underside of the bottom of the barrel in SP performance so far this year. As a result, they skew the results so badly that we need to get rid of them. With this in mind, Pitches per Batter Faced (PBF) is ideally shaped.

What tends to mess things up is SP that fall far into the right side of the distributions. In cases of K/9, you want that. In case of BB/9, you don’t. Overall, the summary breakdown looks like this:

Variable Mean StDev 25% Median 75% IP 24.0 10.2 17.0 26.2 32.0 K/9 8.2 2.4 6.4 8.0 9.9 BB/9 3.5 1.7 2.4 3.3 4.3 BABIP 0.3 0.1 0.2 0.3 0.3 HR/FB 0.1 0.1 0.1 0.1 0.2 ERA 4.57 2.4 2.9 4.1 5.7 TBF 102.8 40.6 74.0 115.0 134.0 SO 22.5 12.2 12.3 23.0 29.0 Pitches 400.1 157.1 278.5 452.0 515.0 PIP 17.15 2.0 15.7 16.9 18.1 PBF 3.90 0.3 3.7 3.9 4.1 LD% 21.2% 0.1 0.2 0.2 0.2 GB% 42.8% 0.1 0.4 0.4 0.5 FB% 36.1% 0.1 0.3 0.4 0.4 SwStr% 9.8% 0.0 0.1 0.1 0.1

Pitchers to Ponder…

I will use WAR as a reasonable shorthand for relative value for SP. The stats that correlate most highly with WAR are (in order): ERA, SwK%, HR/FB, PIP, and BB/9. The higher the SwK% and the lower everything else, the better one’s WAR is. I calculated who was in the top 10% of each category

Variable Mean StDev top 10% IP 24.0 10.2 37.1 K/9 8.2 2.4 11.2 BB/9 3.5 1.7 1.4 BABIP 0.292 0.1 0.205 HR/FB 0.13 0.1 0.026 ERA 4.57 2.4 1.490 TBF 102.8 40.6 154.8 SO 22.5 12.2 38.1 Pitches 400.1 157.1 601.2 PIP 17.15 2.0 14.6 PBF 3.90 0.3 3.6 LD% 21.2% 0.1 12.2% GB% 42.8% 0.1 55.5% FB% 36.1% 0.1 25.3% SwStr% 9.8% 0.0 13.5%

So, how do the top SP in terms of WAR stack up? As of 29 April, the top 25 SP in terms of WAR are:

Name Team WAR Max Scherzer Nationals 1.600 Jacob deGrom Mets 1.400 Gerrit Cole Astros 1.400 Rick Porcello Red Sox 1.400 Dylan Bundy Orioles 1.200 Noah Syndergaard Mets 1.200 Justin Verlander Astros 1.200 Luis Severino Yankees 1.200 Chris Sale Red Sox 1.100 Jose Berrios Twins 1.100 Corey Kluber Indians 1.100 Patrick Corbin Diamondbacks 1.000 Blake Snell Rays 1.000 Alex Wood Dodgers 1.000 Sean Manaea Athletics 1.000 Nick Pivetta Phillies 1.000 Daniel Mengden Athletics 1.000 Lance McCullers Jr. Astros 0.900 Johnny Cueto Giants 0.900 Aaron Nola Phillies 0.900 Trevor Bauer Indians 0.800 Mike Clevinger Indians 0.800 Kenta Maeda Dodgers 0.700 Kyle Gibson Twins 0.700 Jon Gray Rockies 0.700 Clayton Kershaw Dodgers 0.700 Joey Lucchesi Padres 0.700 Tyler Skaggs Angels 0.700 Ivan Nova Pirates 0.700 Marco Gonzales Mariners 0.700 Carlos Martinez Cardinals 0.700 Jason Hammel Royals 0.700

It’s actually the top 32 because everyone from Maeda down is tied at 0.700. Of the top ten, only Porcello (8.32%) and Severino (12.3%) fall out of the top 10% in the league in terms of SwK%. Surprisingly, only Verlander (0.198) falls in the top 10% of the league in terms of BABIP. That does not bode well for him. He’s a great pitcher. But, he is 100 points better than the league average. Expect some regression and, therefore, some of his other indicators to get a bit worse.

Rick Porcello is on a roll because he is not walking anyone (1.1 BB/9) or giving up HR (he gave up his first HR on Sunday 29 April. The data are through 28 April).

Regarding SP who’ve generated lots of chatter…

Sean Manaea keeps an efficient PIP of 13.1. He is walking no one (BB/9: 1.44) and he has a sick ERA of 1.03. Unless he is an X-man or Thanos’s nightmare, he has to regress because he also holds a ridiculous BABIP of 0.148—140 points below the league average. The Astros average BABIP through 28 games is 0.259. Draw your own conclusions.

Patrick Corbin. I like this guy. I really do. But I don’t like him enough for several members of our staff. Sheesh. Get a room. Corbin is in the top 10% in terms of K/9 (12.4), SwK% (16.6) and PIP (14.1). He continues to put the ball on the ground (GB%: 54.1). His BABIP is 0.222. That puts him in the lowest 25% of SP in the league. Like Manaea, he will regress. Arizona’s BABIP is 0.297. Maybe the A’s and Dbacks just put on their A-game when Manaea and Corbin are pitching. Still, the law of averages will catch up with both. They are stellar. But, they are getting tremendous defensive help.

Jose Berrios is in the top ten only in terms of BB/9 (0.85). But, he is in the top 25% in terms of K/9. BABIP, ERA, and PIP. So, he is efficient and is missing bats. Still, Minnesota’s BABIP is 0.274. The Twinkies shine defensively when Berrios pitches.

Luis Severino is not in the top ten in any category. Nevertheless, he is in the top 25 in virtually all categories. So, he is excelling and, yes, benefiting from solid defense. The Yankees normally offer a 0.272 BABIP. For Severino, it’s 0.239. That’s not as big a bump as some of the other guys I’ve noted. Still, it’s also due in part to the fact that he’s keeping LD low (15.6%) and GB% relatively high (50%).

Since I tend to go on about BABIP, I’ll note a couple of guys who continue to suffer despite some quality stats. Do the Dodgers hate Kenta Maeda (13.7 K/9, 2.8 BB/9)? The team BABIP is 0.291. When Maeda’s on the mound, it’s freaking 0.420. Seattle’s Marco Gonzalez (10.7 K/9, 1.6 BB/9) must be wondering the same thing. Maeda has a 14% SwK rate. BUT, like the little girl with a little curl in the middle of her forehead, when these guys are bad… Gonzalez’s LD% is 32. Maeda’s is 26. That puts them firmly in the worst 25% in the league. Maeda’s HR/FB ratio is top 25 (6.7%). But Gonzalez has no problem giving souvenirs to cheap-seat denizens (14.3% HR/FB). Both of these guys are worth watching. If they can put more balls on the ground, they will only improve.

Dylan Bundy suffers from a 0.354 BABIP. While that is dreadful, he can’t take it personally. Baltimore has yet to see a ball it wants to stop (Team BABIP is 0.340). He has quality stats across the board. So, if the O’s can take some more fielding practice, his value will only increase. Lance McCullers, on the other hand, can take this personally. When he is on the mound, the Astros BABIP is 0.333. For the season, it is 0.259. Are they trying to tell him something? Put him on a team with baseball gloves and see what happens…

And for those of you wondering why they bid on Yu Darvish, his line is not that bad. Here is his line so far this year:

IP K/9 BB/9 BABIP HR/FB ERA PIP PBF LD% GB% FB% SwStr% 25.2 10.2 4.56 0.304 11.50% 5.26 19.8 4.3 24.60% 37.70% 37.70% 9.40%

OK. Meh. He is walking too many people and throwing too many pitches per inning. He is slightly above the league average (21.2%) for LD, but not remarkably so. The Cubs’ BABIP is 0.280 and his is 0.304. Again, nothing personal. Over the last four years, his lines are:

K/9 BB/9 BABIP HR/FB ERA PIP PBF LD% GB% FB% SwStr% 2014 11.4 3.06 0.334 8.60% 3.06 16.0 3.8 22.80% 36.30% 40.90% 10.90% 2016 11.8 2.78 0.290 12.00% 3.41 15.8 3.8 19.60% 40.40% 40.00% 12.60% 2017 10.1 2.8 0.283 15.10% 3.86 16.4 4.0 22.40% 40.70% 36.80% 12.3%

The walks are killing him and the SwK% is down. So, hitters are taking pitches. I think there may be much to be said for the impact of his post-season meltdown. Nevertheless, the skill set is still there. So, maybe you can pull the Jedi mind trick and get another owner to part with him while he still looks like a dud.

More to come. Good luck this week.

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Major League Fantasy Baseball Radio Show: Join host Brian Roach, Jr, and John Gozzi live on Sunday April 29th, 2018 from 8-9:30pm EST for episode #118 of Major League Fantasy Baseball Radio. We are a live broadcast that will take callers at 323-870-4395. Press 1 to speak with the host. We will discuss the latest information in the world of fantasy baseball.

Our guest this week is Cole Freel. Cole is a writer with majorleaguefantasysports.com and his articles publish every Saturday afternoon. He will also be co-hosting with Brian starting next Sunday the 6th of May.

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