Archive for Starting Pitchers

2017 Ottoneu FGpts Rankings: SP/RP

We’ve been rolling through our ottoneu FanGraphs points league rankings. This year the rankings will include values from myself, Justin Vibber, and Chad Young. We are presenting our individual dollar values, the average of all three individuals, plus the ranking of that average. In addition the tables below include Ottoneu eligibility (5 games started/10 games played in the prior year). Players are ranked at their most valuable position, and the hierarchy we are using is C/SS/2B/3B/OF/1B (with 3B and OF being a coin toss in terms of replacement level, we chose to include 3B/OF eligibles at 3B).

Prior Rankings: C/1B/3B, 2B/SS, OF

Key:
Split – Difference from highest to lowest $ value
Otto.– Average price across Ottoneu FGpts leagues
AVG. – Average $ value from the four of us
(+/-) – Difference between Ottoneu average price and our average $ value

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ADP to Replacement Player Projected Stats Spreadsheet

Necessity is the mother of invention. –Plato

I wanted to know how owners were valuing Michael Brantley’s playing time. Currently, at NFBC, he is going 233rd overall in NFBC drafts. Over a full season, he is projected to be more productive than the two outfielders going right before him, Carlos Beltran and Randal Grichuk. Owners, via calculations or their gut, are significantly downgrading a full season Brantley. But by how much? I needed to find the league replacement value.

I could go through all the whole league setting and final the values like I did for my Tout Wars league. While I recommend this detailed procedure for any league an owner takes seriously. I was just looking for a quick answer and stumbled upon one while looking over my Fantrax league.

Our friends at FanTrax.com have their players listed with projected stats and ADP. Having both downloadable made a projection sheet quickly come together.

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Cheapish Starting Pitchers: Revisiting the Quadrinity, Plus ADP Mini-Update

It’s time to resume our search for underpriced starting pitchers. For the past two years, we’ve been taking a look at which starters qualify, on the basis of the previous season’s stats, for the Holy Trinity (an established way of looking at stats, relying on a pitcher’s strikeouts per 9 innings, walks per 9 innings, and ground ball percentage), and the Holy Quadrinity (an approach of our own devising, relying on strikeout percentage, walk percentage, soft-hit percentage, and hard-hit percentage).

If you want more background and detail, go here. Obviously, most guys who do well in these categories are going to be top pitchers everyone already knows about. But the approach yields some surprises, including, last season, Justin Verlander and Kyle Hendricks. And, as we determined at the end of last season, in the aggregate it produces some positive value. So let’s see who it turns up this year. Read the rest of this entry »


Mixing Fantasy & Reality: Bellinger & Fastball Velocities

Cody Bellinger is going to be a stud. He’s athletic and can hit the ball a mile. Just watch this home run from yesterday and enjoy.

I believe he’d be getting a ton focus if Adrian Gonzalez, and his contract, didn’t already occupy first base. The 35-year-old is still productive and can’t be benched … I think.

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2017 Lottery Ticket Team: Pitcher’s Edition

This is not a “sleeper” list. Read the rest of this entry »


2017 Pod Projections: Lance McCullers

The Pod Projections are back! My projections are based on the methodology shared in my eBook Projecting X 2.0, and the process continues to evolve and improve.

A couple of months ago, I received my first Pod Projection request from a commenter, and that request was for Astros starting pitcher Lance McCullers. The 23-year-old made his Houston debut in 2015, as he made 22 starts and posted an impressive 3.22 ERA with excellent underlying skills. Unfortunately, he followed up that freshman effort by finding himself on the disabled list for what amounted to about half the season. He dealt with both shoulder and elbow issues, which limited him to just 14 starts. Although his control deserted him, he still posted strong skills, en route to an identical ERA as 2015. Now, he’s the newest member of my 2017 LABR Mixed Draft squad, so let’s find out what I projected his 2017 results to look like.

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2017 New Pitch Tracker

This marks the fourth consecutive spring for tracking new pitches at Fangraphs. In 2014, the series was launched with a piece featuring both a retired and current pitcher and their insight into adding new pitches during the offseason and/or in camp. The 2015 tracking was done at RotoJunkieFix where I serve as the CIO which is just a fancy title for the guy that keeps a 20+ year old fantasy community up and running in his spare time. By popular demand, the 2016 New Pitch Tracker gained front page real estate here and I updated it throughout the spring with help from Jeff Zimmerman and others scraping the stories from the web and the crew at BrooksBaseball helping validate the pitches. That same support model will be in place this year for the extended 2017 Spring Training.

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The 2017 Starting Pitcher Strikeout Rate Downsiders

Nearly a month and a half ago, I shared the names of six starting pitchers who my old xK% metric suggested had the most strikeout rate upside this season, assuming their equation components remained unchanged. I then got sidetracked, introduced an updated version of the equation with new component coefficients and then even played around with incorporating CH% (changeup percentage) into an even newer version of the equation. So I never actually got around to the list of starting pitchers with strikeout rate downside. It’s now time to share those names with you very patient people.

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Eno’s 2017 Pitcher Ranks

I may have taken a step back from RotoGraphs, but I haven’t stopped playing fantasy baseball, and I have to take a look at all the pitchers anyway, and people keep bugging for my ranks in chats and anyway — here they are! I have some notes below the ranks, which are created for 5×5 leagues by using projections and then moving the players around subjectively for different reasons, most of which you will hear on our podcast.

But there are a few notes about tiers and places in the rankings that I like and dislike, notes that might help you think about your pitching strategy this year. Good luck!

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PITCHf/x-Forensics: Alex Reyes

***Note, huge thanks to Jeff Zimmerman for all of his help with this piece***

The sad news that prospective St. Louis Cardinals Ace Alex Reyes was going to miss the 2017 season was devastating news for the Cardinals organization. Reyes looked to make a huge impact in the Cardinals rotation with absolutely devastating Stuff (according to the Stuff Metric, the only starter with better Stuff was New York Mets Starter, Noah Syndergaard). To figure out how Reyes came to break down, let’s look into the scientific literature on UCL injuries.

The first paper I’d like to draw on, was published by David Whiteside and Colleagues, from the University of Michigan (Whiteside et al., 2016). Their method used a machine learning approach, and deduced there were 6 risk factors that could be used to predict UCL reconstruction surgery. These risk factors were 1) Fewer days between consecutive games, 2) smaller repertoire of pitches, 3) a less pronounced horizontal release location, 4) smaller stature, 5) greater mean pitch speed, and 6) greater mean pitch counts per game. How did Alex Reyes measure up in these risk factors?

Reyes started the season at AA, where he started in 14 games and pitched 65.1 innings. At the Major League Level, he pitched 46 innings, and started in 5 games, while appearing in 12 total games. Excluding those pitchers who appeared in less than 10 games in a season, the average days between consecutive games in the MLB in 2016 was 4.37  games.  At the major league level, Reyes had an average of 4.64 games.

How about the repertoire of pitches? In the 2016 season, starting pitchers had on average, 3.5 +/- 0.82 pitches in their repertoire. For a pitch to count as part of the repertoire, I included it in the analysis if it was thrown 10% of the time. Reyes had 4 pitches – A fourseam fastball, two seam fastball, curveball, and change up. These were thrown 35.8, 28.0, 12.0, and 24.2% of the time. So, Reyes threw more than the average number of pitches – so, this isn’t cause for concern based on this study.

How about release location? The horizontal release point league average for Alex’s 4 pitches in 2016, was 1.72 feet – that’s the average absolute horizontal release point (collapsed across righties and lefties). Alex’s release point was 1.74 feet – so, it was actually a more pronounced release point than the league average.

What about stature? Alex Reyes is a tall guy – standing 6’3, and weighing 175 lbs. The league average height for players born since 1985, is 6’1, and the average weight is 209.8 lbs – from the Lahman database. The Whiteside paper only mentions height though, and given that Reyes is taller than most other players, this doesn’t appear to be a risk factor. Reyes is taller than most, but extremely lean at 175 lbs. We’ll come back to this, shortly.
Now, on to the one smoking gun in this paper. Pitch velocity.

Alex had a peak average fastball velocity of 96.8 mph (for his fourseam fastball). That’s a heater, and it represents a fastball velocity with a z-score of 1.51 – well above league average. Why is velocity so stressful? I had written about UCL stress and velocity, using data from Driveline baseball (Sonne, 2016). The fine folks at driveline baseball examined pitch velocity and compared it to predicted UCL stress from the Motus Baseball sleeve. Simply put, as velocity goes up, so does UCL stress (figure 1). In fact, accounting for nothing other than pitch velocity, we were able to explain 37% of the variance in the UCL stress using only pitch velocity – nothing about mechanics, height, or weight.

More recently, those same researchers published data that the UCL stress was reduced when throwing offspeed and breaking pitches, but when normalized to pitch velocity, the stress was much higher in these types of pitches (O’Connell et al., 2017). Reyes throws an 88 mph change up – which could represent significant stress on the UCL based on these data.


Figure 1. Examining the relationship between ball velocity and UCL stress using the Motus Sleeve. Data from driveline baseball (https://www.drivelinebaseball.com/), and article available at http://www.mikesonne.ca/baseball/pitch-velocity-and-ucl-stress-using-the-motus-sleeve-further-interpretation-from-driveline-data/.

So finally, we are left with pitch count per game. Lumping together starters and relievers, the average pitch count per appearance was 45.6. The average pitches per inning was 14.5 in 2016. Reyes had 5 starts, and 7 relief appearances, and his average pitch count per outing was 65.6. Comparatively, his pitches per inning was 16.5 – which could lead to additional fatigue when compared to the league average.

So where do we point to the source of injury? The short answer? We have absolutely no clue.

In the field of ergonomics, we examine injury risk as an interaction of force, posture, and repetition. Workload metrics like pitch counts, and innings counts, give us insight into repetition. The forces can be inferred from the pitch velocity. Where our PITCHf/x data lacks, is giving us insight into the posture, or, the pitching mechanics. A very interesting piece was writen on Viva El Birdos regarding the poor mechanics that Alex Reyes exhibited.

Chris O’Leary has been very active in self promoting his analysis of Reyes’s very risky mechanics, and has predicted for some time that Tommy John Surgery was inevitable for Reyes. The problem baseball is currently faced with, is there is no reliable way of measuring mechanics without the use of motion capture systems. Right now, mechanics are not quantified to the extent they should be, and without a large, public database (like we have for PITCHf/x), it’s hard to completely infer the role that mechanics and timing have when contributing to injury risk.

Early this week on FanGraphs, there was a piece mentioning how Noah Syndergaard’s weight gain could increase his risk of injury (Sawchik, 2017). Compared to Alex Reyes, Syndergaard is a massive man (compared to human beings, he is a massive man). Theoretically, that added muscle mass may in fact keep Syndergaard from getting hurt. That added muscle can help him stabilize his UCL during the pitching motion – an advantage that the slight Alex Reyes did not possess at 175 lbs. During the throwing motion, the stress on the UCL exceeds the known force level for tear of the ligament. It is the role of the muscle to help take some of the stress off of the passive tissues (like the ligaments) during the throwing motion. Of course, someone like Chris Sale tends to be the outlier that challenges this hypothesis.

With respect to the workload Alex Reyes faced – he pitched less than 120 innings at all levels in the 2016 season. This alone does not represent an elevated risk of injury. What we can’t see from the PITCHf/x data, is how his workload variability changed from moving from a pure starter role at the minor league level, to a reliever and starter at the major league level. If you would like to delve into some mind blowing hypotheses on injury, check out the webinar from the Baseball Performance Group. They identify that it may be the variability in workload that poses a risk to pitchers – and not the overall workload itself. Moving between different roles would definitely increase the variability in rest times for Reyes.

Assessing the injury risk of pitchers is a challenging proposition. There is no single silver bullet, but understanding the scientific literature and examining the role of multiple factors is the way forward in trying to determine what might have gone wrong.

References

Whiteside, D., Martini, D. N., Lepley, A. S., Zernicke, R. F., & Goulet, G. C. (2016). Predictors of ulnar collateral ligament reconstruction in Major League Baseball pitchers. The American journal of sports medicine, 44(9), 2202-2209.

O’Leary, C. (2017). Pitching Mechanics Overview Alex Reyes. Retrieved from http://chrisoleary.com/pitching/PIP/Overviews/Reyes_Alex_PitchingMechanics.html, on February 16, 2017.

Sonne, M. (2016). Pitch Velocity and UCL Stress using the Motus Sleeve: Further Interpretation from Driveline Data. Retrieved from http://www.mikesonne.ca/baseball/pitch-velocity-and-ucl-stress-using-the-motus-sleeve-further-interpretation-from-driveline-data/, February 16, 2017.

O’Connell, M, Marsh, J., Boddy, K., (2017). Fastballs vs. Offspeed Pitches – Comparative and Relative Elbow Stress. Retrieved from https://www.drivelinebaseball.com/2017/02/fastballs-offspeed-pitches-comparative-relative-elbow-stress/, February 15, 2017.

Sawchik, T., (2017). Thor is Bigger, Stronger… and Riskier? Retrieved from http://www.fangraphs.com/blogs/thor-is-bigger-stronger-and-riskier/, February 15, 2017.

The Red Baron, (2017). The Changing Mechanics of Alex Reyes. Retrieved from http://www.vivaelbirdos.com/2017/2/15/14613328/the-changing-mechanics-of-alex-reyes-delivery-breakdown-carlos-martinez-injury, February 15, 2017.