I’m cleaning up any news I have a backlog because I’m off on vacation next week and hopefully when I return, a decision will exist on an MLB season. As a reminder, the focus of this article is to dive deeper than the headline news like Chris Archer’s surgery.

General information

The effects of a concussion can still be felt two years later.

Interesting nugget on #concussions. Remember this when you have an athlete that suffered a concussion less than 2 years ago… pic.twitter.com/y70wfYiuPt

— Jesse Morse, MD (@DrJesseMorse) May 1, 2020

Here is a list of players who have been on the IL for a concussion over the past two years.
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In the final part of my latest injury investigation, I trying to see if pitchers who have accumulated a certain amount of injuries age worse than those who have stayed healthy. And if so, are there any rules-of-thumb that can be used. I’ve already examined chronically injured hitters and if accumulated days missed for pitchers lead to more Injured List (IL) trips. The results aren’t groundbreaking findings that constantly hurt pitchers declining faster at certain thresholds but now some numbers can be added to the narratives.

My overall goal is to see the accumulative effect of various injuries can lead to a pitcher aging faster. The factors I had never accounted for are accumulated IL days and times of the IL for elbow, shoulder, or arm injury. Also, I’m only diving into starters (GS/G >= .5) from 2010 to 2018 because relievers, especially closers, are already tough to project. I divided the starters by their age based on a steep production decline starting at age 29. For the pitcher’s talent level, I used ERA- that increase, like ERA, as a pitcher performs worse. The results were a little mixed.

One item to keep in mind, pitchers have historically, maintained their production, or declined as they age. While there is always the exception of a pitcher improving, most are headed down with the average change of 2.8 points of ERA- a year.

What I found from this data run and others not listed, age doesn’t matter. Also, while the average IL days steadily climb, the ERA- value jump seems to increase except when it doesn’t. I simplified the results and settled on a 120-day threshold with the following results.

Once a pitcher goes over the 120-day threshold (i.e. a full MLB season), their career declines at a faster than expected rate. Again, there are always going to expectations but rostering too many of these hurt starters increases the downside potential.

Now for one more angle that I had jotted in my to-do book. Most major pitcher injuries center around the arm, so I decided to focus just on them. I bucketed the information by the number of times a pitcher was on the IL for a general arm (e.g. forearm), elbow, or shoulder injury (no wrist or hand). With more than 99% of all instances in the single digits, a simple workable division was easy to find at 2 IL stints.

Even pitchers who had two or few IL stints weren’t in great shape with them averaging over 200 days on the IL. That third arm related IL trip can be a deal-breaker because the pitcher will, on average, will see their skill degrade about twice as fast as those with two or fewer trips.

And finally here are the pitchers who have over 120 days on the IL and three or more arm related IL stints (min 10 IP last season).

Several high ADP names fill the list like Morton, Darvish, Strasburg, Kershaw, and Cole. Does this information mean I won’t roster the pitcher? Maybe. With a fantasy team only starting nine pitchers, I’d like those pitchers to be as rock-solid as possible with little chance of decline. The downside means that I will need them to come with a discount and is an easy tiebreaker. That’s not helpful since that’s everyone’s injury take.

My stance on the information is wishy-washy because I am unsure. I haven’t fathomed a way to weight the information especially if I want to use it to create auction prices. I need to find a way to change ERA- to fantasy-relevant stats. It wouldn’t be that hard but I’m looking at two different inputs (total days and arm related trips). Also, I should incorporate possible time missed from previous IL trips. I’m going to let the information stew for a bit and unless I come to some divine revelation, I’ll perform a forced dive once this season is over or canceled.

I had no plans to write or investigate pitcher injuries again. I’ve done it several times in the past with similar results. Since I needed the same information to investigate if an often injured pitcher ages faster as I did with hitters, I had the data available so why not take another stab at projecting pitcher injury risks with a few different inputs.

For a refresher, here are some of my previous findings:

• Previous injuries, age, and workload matter.
• A low Zone% is a precursor to injuries
• High fastball velocity, not pitch type, leads to injuries.
• Shoulder and elbow injuries can linger for a while.

The small data difference is that instead of limiting the IL days to the previous one to three seasons, I’m just using the accumulated days. Also, I tracking the number of times the pitcher went on the IL for an arm, elbow, or shoulder injury. The two different factors are joined by fastball velocity, Zone%, and age to see what leads to injuries the next season.

I took all the data from all the pitchers and ran it through a Trees analysis and got the following chart.

This image sums up pitcher injuries perfectly. The best predictor of future injuries is past injuries. And just because a pitcher had never been on the IL, on average, they will still spend ~18 days on it. It’s just re-enforcing common sense backed up by study after study.

From my previous work, the injury rates between starters and relievers (i.e. starters who can’t stay healthy) are drastically different. For that reason, I ran the analysis splitting out starters (GS/G >= .5) from relievers (GS/G < .5). Here are the two decision trees.

Starters

Relievers

We have some further division taking place fastball velocity on both, a further out 460-day threshold for starters, and age requirement. I’m not a huge fan of the multi-branched tree with many variables. I’m all for keeping it simple. Using the above variables, I cut and diced the data into several possible combinations and came up with the following divisions.

Again, the rates are similar to my previous findings. The only changes are the pitch velocity groupings and that rough over-460 IL day group who average two months on the IL a year. For me, I focus on starters and will designate the starters into three risk groups:

• Low: No IL, low velo.
• Medium: No IL, high velo, and some IL, low velo.
• High: Some IL, high velo, and high IL.

Not all injuries can be avoided, but the injury downside is just another factor to consider when setting each pitcher’s fantasy value.

And what’s a study without the players to consider for the upcoming season. Here are the historic IL days and fastball velocity for any pitcher with 10 starts last season.

• The pitcher with the highest velocity and IL experience is Noah Syndergaard. That 2020 IL stint didn’t take long.
• The oldest starter to never have been on the IL is Tanner Roark at 33.
• Darvish and Morton are going as the 17th and 18th pitchers even though they’ve broken the 460-day threshold.
• Just go and scroll through the starters who have been on the IL and throw over 93-mph, especially over 95. Lots of them have spent considerable time on the IL over their careers. I’m thinking to target “safer” but elite starters if given the opportunity like Corbin, Bieber, Kershaw, Castillo, and Flaherty. There is no way to completely stay away from the injury risk but why not add a pitcher with a 28% chance (Boyd) than someone with a 63% chance (Ryu)

These conclusions were about 80% in line with what I expected with fastball velocity nudging itself in. Next up will be taking this information and seeing if a higher injury rate ages pitchers more than projected.

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One of my Launch Angle Podcast partners, Rob Silver, brought up how if there is a universal DH, the NL pitcher will no longer face ineffective bat-wielding pitchers. Simply, pitchers can’t hit. Last season in 4789 PA, National League pitchers hit for a combined .126/.157/.160. Our own Dan Szymborski continued the discussion to see if dominating pitchers hitting was a repeatable trait. I’m going to go a different route to investigate, using Dan’s information, how a pitcher’s projection would change going to an American League team (effectively including a DH) and this number affects a pitcher ranking.

I’m going to start off saying to not take any of the following information as the gospel truth. I’m trying to achieve a better projection that’ll be closer to the final outcome. Each stat and step in the process can be nitpicked along the way. I’m not even sure if the following method is the best way but it’s a way. I’m trying to move the discussion from “The DH will be a try breaker for me when drafting” (quote from a podcast I heard) to actually putting some number behind the possible changes.

Also, I’m not here to argue on why Jacob deGrom started out as the 8th ranked starter and he’s now 9th. I just collect a projection set. Anyone who uses stats to generate their projections will have their own secret sauce. I have my own. I just need a projection framework and live with it. Here is how I set it up.

I downloaded the 2020 ZiPS projections from here at FanGraphs. I used the ZiPS values since Dan created them and I’ll be using the inter-league adjustments provide in his article.

Then I changed each pitcher’s stats using Dan’s 2019 variables.

Variable: Change

• BB%: +4%
• K%: -5%
• AVG: +.007
• RC/G: +13%

I just adjusted the pitcher’s projected stats by the above values and created a hits estimate from the AVG with few assumptions.

NL pitcher innings projections have two offsetting values that could also be in play. The worse results could lead to fewer innings thrown (i.e. early hook) and the pitcher’s value could drop. On the other hand, the times a pitcher nearing his pitch limit will be replaced by a pinch batter will disappear. One of the two factors will likely dominate

Next, I used the 2019 12-team SGP (Standings Gain Points) formula from The Process to create pitcher valuations. The SGP value is the expected jump in the standings if that pitcher’s stats are added to a team’s stats. Here are results from the final top-40 starting pitcher using the SGP formula and ZiPS projections (I’m not sure why the TJS pitchers are still included but I don’t get paid the big bucks to know such things).

The changes are significant once all three factors (WHIP, ERA, strikeouts) are factored in. While the rank changes by just one or two with the top-10 or so arms, the difference becomes significant around pick 20 with moves of four spots. Maybe this change is a tie-breaker for some owners, but if an owner gains an extra ~1 SGP from all nine pitchers, it becomes nine spots in the standings. I think every owner would take those extra spots.

Just eyeballing the differences, it’s ~0.40 increase in ERA and 0.04 bump in WHIP to go with the 5% drop in strikeouts. The near half run increase in ERA will scare off quite a few owners by itself. Other owners will get blow off the possible changes, but in my current opinion, they will be playing catch up if they ignore them.

Again, don’t take my word for it … I’m still coming to grips with Lance Lynn possibly jumping Patrick Corbin. I could be wrong with these calculations but hopefully, some other analysts will step up and perform the calculations. The possible change in production is likely the biggest valuation change with half the pitchers facing legit MLB hitters instead of the irrelevant pitcher.

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Predicting hitter injuries has been a fool’s errand for me. Besides players with chronic injuries (e.g. Albert Pujols and Ryan Braun), others and myself have made little headway in the field. With few guidelines, many fantasy analysts and owners handle hitter injuries differently. Previously, I focused on a hitter’s recent injury history. This time I attempted a different approach and used the hitter’s career IL days. In the end, I found a useful and easy to remember injury threshold.

For the study, I examined hitters from the 2010 to 2018 seasons. I have IL data going back to 2002, so I hoped the preceding eight years of data would get most of the hitter’s 2010 career total. Additionally, I needed the next season (e.g. 2019) to compare results. Additionally, I set a minimum hitting threshold (100 PA) to include at least some semi-regulars. I know I may miss a hitter who is out the whole season, but the two-week callups were diluting the results. In all, I ended up with a sample of 2365 player seasons.
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Note: This article was written in two parts, with the first half being before the draft and the second half after completion.

Prep

Tonight, I’m participating in a 1999 retro with several other industry analysts. The premise is simple: the owner drafts a 5×5 roto team based on the 1999 season’s final player stats. That’s where the simplicity ends.

I knew these drafts were going on but as I was busy with other projects, I hadn’t dived into them. Then Fred Zinkie contacted me to do an idiot check on his valuations for the draft that happened last Wednesday. I’m a fan of using SGP (standings gain points) for my normal evaluations, but none were available for 1999. Instead, I had to break out a copy of The Process and create the player valuations based on the Z-score method. (Z-score looks at how much a player’s real or predicted stats are above or below the league average for the draftable player pool. It takes several passes to get the correct valuations since the final player pool is unknown. The z-score method is helpful when no league history exists.)

After I was done, we noticed two differences. Fred used a modified SGP for the season and was valuing stolen bases a little more. We aren’t sure of the cause, but he gave catcher and middle infield a little more of a bump. I think the difference was from the different stolen base values. Read the rest of this entry »

About every month, podcast mate Rob Silver pours out his undying love and affection for the Rockies Charlie Blackmon. I’m not as much of Blackmon fan but this comment got me thinking.

To play devil’s advocate:

his barrel% went up.

His exit velocity went up.

His xBA and xSLG went up.

Hard hit% went up.

K% went down.

Prior to last year, he hit 28 HRs with 105 runs in his last 161 road games.

It’s possible last year’s road stats were just noise.

— Rob Silver (@RobSilver) May 10, 2020

Blackmon definitely hit the ball harder last year but so did everyone else with MLB’s juiced ball. Even with noisy data, Rob was right and Blackmon exceeded expectations.
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