I have finally gotten around to compiling the 2014 disabled list data. Usually I get this information out in October, but instead I was driving to and watching this unique event I have never seen live in Kansas City called postseason baseball. Crazy stuff. Now I can get back to the boring stuff involving spreadsheets and SQL. Besides compiling the 2014 DL data, I have dived into some other topics I have wanted to look at for while, such as historic team values, injury rates for various injuries–especially to pitchers–and how certain injuries affect a player’s performance.

At times, the following information can seem like just that, information. I started off on a few tangents but limited the amount of research. One such tangent ended up as entire separate article to be seen in the future here at The Hardball Times. If I did everything I wanted/could have done, I would have ended up with a small book, so I had to draw the line somewhere. I’m hoping people can find pieces of information to use to help explain the never-ending stories surrounding baseball.

2014 Team Data

Let’s look at how each team stood in terms of number of trips to the DL and total days lost. I collected the 2014 data from the player transactions at MLB.com. It, along with the 2010 to 2013 data, is available at Baseballheatmaps.com. Let me know if you find any discrepancies in the data.

• Congrats to the Brewers for having the fewest number of DL trips. The Pirates had the fewest number of lost days at 409.

• Now take the Pirates total, multiply it by five and it would still be smaller than the number of days lost by the Rangers. The Rangers total of 2,116 days lost was the highest total going back to 2002, 99 more than the Diamondbacks had in 2004.

Total Disabled Days Lost

Team (Year) Total Days Rangers (2014) 2116 Diamondbacks (2004) 2017 Padres (2012) 1973 Royals (2007) 1857 Rangers (2004) 1811 Nationals (2006) 1755 Red Sox (2012) 1669 Mets (2008) 1662 Athletics (2010) 1647 Marlins (2008) 1633

The Rangers just need to put the 2014 season behind them and look to the future.

• It was the best of times for the Braves. The smallest number of position player DL days. It was the worst of times for them also. The largest number of days lost for pitchers. I went back and looked to see if other teams ever exhibited such differences in days from hitters and pitchers. Here are the top 10 teams:

Total Disabled Days Lost, Difference between Hitters and Pitchers

Team Season Pitchers Hitters Absolute Difference Orioles 2008 1377 102 1275 Mariners 2007 1075 0 1075 Braves 2014 1033 22 1011 Rangers 2008 1168 214 954 Nationals 2006 1335 420 915 Mets 2013 1006 185 821 Yankees 2013 350 1170 820 Rockies 2009 924 116 808 Orioles 2007 1003 207 796 Braves 2008 1110 319 791

The Braves have the third-highest total, with the 2008 Orioles having the top value and the 2007 Mariners coming in second with zero hitters on the DL. The 2013 Yankees were the only team to make the top 10 with hitters being the higher value. The next team with hitter DL days being the higher category was the 2008 Nationals.

2002 to 2014 DL Trends

Now, the 2014 data can be compared to previous seasons. Here are the total days lost since 2002:

Looking at the data, the days lost to hitters is lower in number and more consistent from season to season than the days lost by pitchers.

Besides the league-wide numbers, here are the team totals from the entire time frame (2002-2014), last five seasons and last three seasons.

• The White Sox’ dominance of not putting players on the DL finally took a small hit. They still hold the overall lead in least days lost, but over the past three seasons, the Twins and Mariners had the two lowest values.

• Speaking of the White Sox, it seems the AL Central took a lesson from the White Sox in keeping their players healthy. From 2010 to 2014, five of the six lowest totals are from the AL Central. Here is how the five teams did before and after 2010:

Average Disabled Days Lost, AL Central, 2002-2014

Team Average (2010-2014) Average (2002-2009) Difference Royals 698 1078 -380 Tigers 713 934 -220 Indians 738 842 -104 Twins 717 709 8 White Sox 556 420 136

• Historically the Twins have had low DL numbers, and their values have stayed fairly constant. The Royals, Tigers and Indians have seen their number of DL days drop immensely. I wonder if they were able to copy the White Sox in some ways to keep their players healthy or if it was just a coincidence. The one item this group generally has in common is they have young pre-abitration players and not many old, injured veterans.

• The list of the teams with the most DL days is filled with teams with large checkbooks that can afford old, declining stars. Well, except for the Padres; I don’t know what’s going on there–maybe too much Carlos Quentin. Old, veteran teams should not be surprised if quite a few of their players are DL bound.

Besides the overall trends, millions of possible combinations could exist when comparing teams and the league-average values. Instead of creating even more graphs, here is one interactive graph that allows the user to select whatever team(s) he or she likes for comparison. I have set the initial view to the teams with the most, fewest and average days on the DL.

Changing Dynamic of Pitcher Injuries

For pitchers, I had an inclination that shoulder injuries have been declining while elbow injuries are the rise. And it is true as seen here.

Days lost to shoulder injuries reached almost 7,000 in 2008. In 2014, the total days lost was under 3,000. Much of this improvement can be attributed to better exercises for the muscles in the shoulder.

So with the number of shoulder injuries down, something had to give. The number of days lost to elbow injuries went from about 5,000 days in 2008 to over 8,000 in 2014. The days lost just seem to be transferring from the shoulder to the elbow.

The difference among teams is also staggering. Here are the number of days lost on or before 2008 and after 2008.

Total Disabled Days Lost, Shoulder vs. Elbow, 2002-2014

Shoulder Elbow Team 2002-2008 2009-2014 Diff 2002-2008 2009-2014 Diff Angels 167 193 26 74 158 84 Astros 79 220 141 131 135 4 Athletics 116 125 9 122 425 303 Blue Jays 236 318 82 90 198 108 Braves 96 106 10 249 362 113 Brewers 223 116 -107 82 120 37 Cardinals 217 195 -22 179 128 -50 Cubs 218 121 -97 236 259 23 Diamondbacks 135 154 18 104 216 112 Dodgers 220 181 -39 154 365 211 Giants 84 46 -39 135 121 -14 Indians 97 19 -78 256 240 -15 Mariners 170 177 7 212 112 -100 Marlins 166 131 -35 295 240 -56 Mets 242 288 46 205 191 -15 Nationals 324 212 -112 184 183 -1 Orioles 282 118 -164 283 87 -196 Padres 180 181 217 385 168 Phillies 177 122 -56 189 228 39 Pirates 171 252 81 107 105 -2 Rangers 215 183 -32 301 268 -33 Rays 219 100 -119 83 156 72 Red Sox 127 71 -56 153 159 6 Reds 293 191 -102 110 116 6 Rockies 220 206 -14 116 234 118 Royals 238 70 -168 160 247 87 Tigers 208 119 -89 143 233 90 Twins 78 135 56 230 142 -88 White Sox 74 115 41 44 79 35 Yankees 204 245 41 156 132 -24

Two major points stick out. First, the Astros, Blue Jays, Pirates, Mets and Yankees need to figure out what the other teams are doing to improve shoulder health and get on board. Second, what are the Orioles doing to improve both shoulder and elbow health? Dave Brown asked Buck Showalter about this trend; here is some of what he said.

There are some ways that you can reduce your risk factor. A lot of it has to do with long before you get them, with all of the abuse they get from some of these travel teams around baseball. We’ve just been real consistent. In our situation, knowing who we are and what we can and can’t do with player acquisition (relating to money), we have to be able to grow our own pitchers. We have to be able to protect them, and we’re not going to stray from that. It’s just like, we’re going to teach a guy to throw a change-up or have better command of a fastball, and we’re also going teach him how to be as healthy as you can. Because I’m in charge, as a lot of people are, of protecting our commodities. Not that ours are any more precious than anybody else’s, but this is where we’re going. These are our pitchers. If we can keep them healthy, we’re a better team. We’re not reinventing the wheel. I just think our whole organization has stayed very consistent through it. We may have a year, next year, where it doesn’t happen that way. It’s kind of cyclical. But we’re trying to do everything we can to be consistent. Our pitching coaches in the minor leagues have been consistent from top to bottom with managing innings and managing pitches and exercises that we do to try and eliminate as many problems as you can, knowing that you’re not going to fully solve it, ever, until you change the anatomy of the arm and put it where you walk around like this (waves arms straight over head).

Baltimore has sent players to the DL around 350 fewer days over the last six seasons than the seven before them. The team is doing something right.

Effects of Injuries

This is a study I have wanted to do for a while: compare the results of different injuries from the season before to the season of the injury and the season after. I grouped the data by different body locations and by time on the DL (more or fewer than 30 days). I easily could have divided the data into more specific injury types, but for now I lumped the data into large groups.

To examine the data correctly, I needed to create some baseline aging factors. Most of the players headed to the DL are older and on the downward slope of their careers (average age around 29). I created aging curves for players who never spent time on the DL between the two ages in question. Here is the aging curve of players who were not on the DL at either age and the entire population.

Note: The aging curve was created by the delta method by weighting plate appearances using their harmonic means. With this method, there’s a small survivor bias summarized by Mitchel Lichtman here at the Hardball Times:

…survivor bias, an inherent defect in the delta method, which is that the pool of players who see the light of day at the end of a season (and live to play another day the following year) tend to have gotten lucky in Year 1 and will see a “false” drop in Year 2 even if their true talent were to remain the same. This survivor bias will tend to push down the overall peak age and magnify the decrease in performance (or mitigate the increase) at all age intervals.

The key numbers to take from the above graph are the healthy values around the average age of the players being examined.

Starting with hitters, I looked at how their batting average, on-base percentage, slugging percentage and isolated power change in three different ways.

Year before the injury to year of injury

Year of injury to year after the injury

Year before the injury to year after the injury

Using the overall numbers (available here), hitters performed worse in the season they were injured than the season before because…WARNING: ROCKET SCIENCE…they were hurt. The key, then, is how much they will bounce back once healthy. Here is how hitters over- or under-performed their age-adjusted OPS comparing their year-before season to their year-after season.

Change in Age-Adjusted OPS, On DL 30 days or fewer

Injury Location Change in OPS Arm -0.054 Head -0.040 Elbow -0.031 Ankle -0.019 Hand/Fingers -0.012 Back -0.008 Leg -0.001 Abdomen 0.001 Shoulder 0.003 Foot/toe 0.004 Neck 0.006 Hip 0.010 Wrist 0.010 Knee 0.015 Groin 0.020

Change in Age-Adjusted OPS, On DL Greater than 30 days

Injury Location Change in OPS Elbow -0.056 Neck -0.030 Wrist -0.028 Arm -0.027 Head -0.024 Shoulder -0.019 Leg -0.017 Knee -0.012 Hip -0.010 Hand/Fingers -0.007 Ankle -0.004 Back -0.003 Foot/toe 0.007 Abdomen 0.018 Groin 0.045

• Arm issues have the largest effect on short stays and elbow on long stays. Elbow injuries would include Tommy John surgeries, so it’s apparent why such injuries would require longer stays. Arm, elbow and wrist issues seems to have more of a long-lasting effect than other injury types.

• Head issues, which are mainly concussions, have more of an effect on the players’ continued production after a short stay versus a long stay.

• It is interesting that players who take time off for groin issues see a huge improvement. I wonder if the players suffered through the problem for more than one season before finally dealt with it.

Now on to pitchers. For them, I looked at walk and strikeout rates, ERA and fastball speed (FBv) over the same three time frames for pitchers. As with the hitters, I created an aging curve for both healthy pitchers and the overall population.

The average age for pitchers suffering injuries is in their late 20s to early 30s. During this time, “healthy” pitchers experienced some decline, and here are the average values for these non-hurting pitchers:

Average Change for Healthy Pitchers

K/9: -0.26

BB/9: + 0.03

ERA: + 0.22

FBv: -0.37

Knowing that pitchers will be on the decline even if they don’t go on the DL, here are the age-adjusted overall numbers from the year before the injury to the year after (wrist, head and neck injuries were removed due to lack of information). Full list available here.

Change in Age-Adjusted Performance, On DL 30 days or fewer

Injury ERA K/9 BB/9 Fbv Hip 0.83 -0.54 0.08 -0.56 Hand/Fingers 0.81 -0.89 0.26 -0.53 Arm 0.38 0.04 0.27 0.35 Shoulder 0.36 -0.21 0.13 0.01 All 0.31 -0.15 0.18 -0.18 Knee 0.29 -0.08 0.37 -0.35 Back 0.24 0.11 0.12 -0.41 Foot/toe 0.23 0.21 0.03 0.29 Elbow 0.06 -0.26 0.33 0.01 Groin 0.04 -0.24 0.03 0.01 Abdomen 0.00 0.05 0.05 -0.08 Ankle -0.11 -0.13 -0.23 -0.26 Leg -0.24 0.86 -0.13 0.14

Change in Age-Adjusted Performance, On DL greater than 30 days

Injury ERA K/9 BB/9 Fbv Ankle 1.06 -0.41 0.28 0.09 Hip 0.77 0.20 0.98 0.06 Foot/toe 0.50 -0.19 0.23 -0.59 Arm 0.38 0.11 0.06 -0.07 Knee 0.32 -0.37 0.55 -0.90 All 0.31 -0.19 0.14 -0.28 Shoulder 0.29 -0.08 0.14 -0.13 Hand/Fingers 0.26 -0.41 0.20 -0.04 Back 0.23 -0.11 0.19 -0.32 Leg 0.14 -0.88 -0.06 -0.43 Abdomen 0.03 -0.27 0.03 -0.07 Elbow 0.03 -0.17 -0.03 0.03 Groin -0.14 -0.09 -0.35 0.41

• Looking at the overall numbers, it’s no surprise seeing pitchers performing worse after injuries than before.

• Concentrating on the leading causes of time missed, elbow and shoulder issues, shoulder injuries seem to linger the longest. If a pitcher spends 30 days on the DL for an elbow injury, he comes back almost the same as before the injury. A short shoulder stint seems to be a sneaky issue, with an additional 0.36 increase in ERA and worsening of BB/9 and K/9. However, with velocity staying constant, the injury may be masked.

Conclusion

This is a ton of information to digest, but I hope it answered a few questions and raised even more:

• the 2014 data

• recent trends

• overall team data

• the rise in shoulder injuries

• healthy aging curves

• how disabled stints affect performance

Every time I look into injury data, I find something I never knew before. This time was no different. Injury effects is one of the few under-analyzed areas in the sabermetric community, and one with much to gain. I hope Iwas able to shed some light on the subject.

References and Resources