Early Season Pitcher Workloads

Traditional pitching metrics, such as innings pitched, and pitch counts, have often missed the mark when it comes to preventing pitcher injuries. As a result, I developed the Fatigue Units metric – which shows promise in illustrating how extreme workloads can influence pitchers in the subsequent seasons.

As a quick refresher – Fatigue Units are calculated by looking at an interaction between the number of pitches thrown, the velocity they are thrown at, the time taken between pitches, and the number of days between appearances. In the 2015 and 2016 season – these were your FU leaders.

2015 and 2016 Fatigue Units
Rank Name 2015 2016 Total
1 Travis Wood 24.48 20.13 44.61
2 Dellin Betances 24.13 20.15 44.28
3 Chris Sale 21.92 21.51 43.43
4 Max Scherzer 20.38 20.16 40.54
5 Chris Archer 21.18 18.93 40.11
6 Johnny Cueto 21.85 17.92 39.77
7 Jeurys Familia 21.04 17.97 39.02
8 Yordano Ventura 19.49 19.24 38.73
9 Jake Arrieta 21.70 16.55 38.25
10 Randall Delgado 19.26 18.71 37.98
11 Roberto Osuna 18.00 19.82 37.82
12 Cole Hamels 19.93 17.57 37.50
13 Brad Brach 18.14 19.15 37.29
14 Zach Duke 17.12 19.84 36.97
15 Addison Reed 15.54 21.17 36.72
16 David Price 19.45 17.22 36.67
17 Erasmo Ramirez 17.74 18.83 36.57
18 Hector Santiago 19.95 16.60 36.55
19 Kyle Barraclough 15.99 20.50 36.48
20 Madison Bumgarner 18.35 18.03 36.38

Looking at the 2017 data for highest workloads, some pitchers have already starting racking up the fatigue units. Let’s dive in to see who has the highest workloads, and what teams appear to be mitigating those effects.

2017 Individual Fatigue Units and Workloads
Rank Name Fatigue Units Days Between Back to Backs IP Total Pitches Game Apps Pace (s) Start IP Relief IP
1 Felipe Rivero 6.20 2.00 8 19 297 19 21.6 19
2 Enny Romero 5.71 2.62 5 15.1 276 15 24.5 15.1
3 Brad Brach 5.57 2.06 7 18.2 297 18 23.8 18.2
4 Fernando Salas 5.31 2.06 7 15.1 287 18 25.9 15.1
5 Danny Farquhar 5.18 2.18 6 15 288 18 23.1 15
6 Bud Norris 5.06 2.25 5 18 306 17 27.6 18
7 Anthony Swarzak 4.96 2.09 5 14.2 195 12 25.3 14.2
8 Jhan Marinez 4.89 2.77 5 14 274 14 26.7 14
9 Joe Kelly 4.87 2.62 2 17 290 14 27.8 17
10 Yusmeiro Petit 4.82 2.91 3 19 296 12 24.5 19
11 Chris Sale 4.81 5.33 0 51.2 757 7 20.4 51.2
12 Tyler Clippard 4.78 2.27 6 14.1 227 16 27 14.1
13 Josh Smoker 4.71 2.29 2 16 311 15 22.4 16
14 Seung Hwan Oh 4.66 2.64 6 16.2 285 15 22.9 16.2
15 Brian Duensing 4.64 2.27 4 14 210 12 22.9 14
16 Miguel Diaz 4.61 2.57 3 15.1 260 15 24.8 15.1
17 Daniel Hudson 4.59 2.25 5 14.1 275 17 27.6 14.1
18 Joely Rodriguez 4.58 2.43 4 17.2 287 16 23.3 17.2
19 Chris Devenski 4.56 3.40 2 21 328 11 21.2 21
20 Hansel Robles 4.53 2.25 5 18.1 302 17 24.4 18.1

Felipe Rivero leads the MLB in workload so far, driven primarily by an astonishing 8 back to back appearances in 19 games. That is not a lot of time for recovery! He averages an outing once every 2 days – also the shortest in the MLB. It’s easy to see why though – he has an ERA under 1, on a team that has a historic number of blown leads so far. There’s a reason why certain pitchers can get to high workloads – they’re good.

Brad Brach is also sky rocketing up the workload charts with the injury to Zach Britton – and has appeared in 7 back to back games. These are very high workloads early in the season, but should tend to decrease as their respective teams either start winning games big, or losing games big.

2017 Team Fatigue Units and Workloads
Rank Team Fatigue Units Days Between Back to Backs IP Total Pitches Game Apps Pace (s) Start IP Relief IP
1 Mets 48.97 3.54 41 293.6 5052 159 22.93 173 119.9
2 Pirates 44.04 3.89 21 291.1 4776 124 23.20 182.2 108.9
3 Cubs 43.57 3.70 18 305.2 5268 147 22.52 176.4 128.8
4 Angels 43.36 3.93 18 310.1 5128 142 24.69 191.8 118.3
5 Padres 42.49 4.01 16 291.9 4788 134 22.56 184 106.5
6 Diamondbacks 42.40 3.66 19 296.5 5057 133 23.72 194.4 102.1
7 Marlins 41.73 3.79 21 284.2 4864 140 23.61 160.6 123.6
8 Rockies 41.53 3.79 14 304.2 4935 143 23.44 191.4 112.8
9 Cardinals 41.00 3.84 19 288.5 4798 137 22.96 188.5 100
10 Orioles 40.73 4.23 23 286.2 5027 129 24.13 173.7 112.5
11 Rays 40.23 3.90 23 309.7 5163 142 26.26 197.3 112.4
12 Blue Jays 40.18 3.85 17 296.4 4931 146 24.46 178.6 117.8
13 Brewers 39.98 3.84 26 279.7 4862 139 24.81 169.9 109.8
14 Dodgers 39.96 4.03 19 292.2 4755 138 25.92 183.5 108.7
15 Nationals 39.85 3.80 16 296 4985 132 24.09 201.1 94.9
16 Giants 39.78 3.84 18 297.6 4893 139 24.34 200.5 97.1
17 Mariners 39.76 3.74 15 291.2 4745 142 23.69 175.9 114.6
18 Athletics 39.16 4.20 15 287.7 4825 131 25.02 175.8 111.9
19 Reds 39.04 4.19 8 292.5 4906 131 21.89 162.4 130.1
20 Rangers 38.51 4.17 15 298.3 4972 132 24.49 198.9 99.4
21 Yankees 38.11 4.21 16 280.5 4525 123 23.54 183.6 96.9
22 Astros 37.98 4.06 14 297.6 4804 127 24.72 194.8 102.8
23 Indians 37.38 4.13 17 277.5 4610 121 23.27 186.7 90.8
24 Royals 37.20 4.05 16 286.5 4774 132 22.57 180 105.8
25 Red Sox 37.07 3.91 13 282.1 4787 128 25.30 186.4 95.7
26 Phillies 35.07 4.10 16 274.5 4591 127 23.74 169.6 104.9
27 Twins 34.92 4.15 14 263.5 4417 132 23.80 158.6 104.9
28 White Sox 34.78 4.03 15 268 4458 115 25.17 176.7 91.3
29 Tigers 33.70 3.66 15 269.7 4823 125 25.74 178.5 91.2
30 Braves 33.59 3.51 18 266.4 4293 127 22.78 169.8 96.6

When you look at the teams with the highest workloads, something very dramatic jumps out at you – the Mets already have 41 back to back appearances out of their bullpen. The next closest? The Brewers, with 26 back to back appearances. This is a landslide! Quite honestly, it brings to question the management of the bullpen – and as far as risk factors go, they have the second shortest time between pitching appearances – 3.54 days between appearance.

Of course – this is speculation when it comes to evaluating bullpens – particularly in the early going. Bad performances by the bullpen can really tax the pitchers who are performing in the early onset of the season – take for example, Felipe Rivero this year, and Roberto Osuna/ Joe Biagini last year. Skippers will turn to the guys who can get them the outs they require to finish off games. Over a long season – this tends to balance out. If not? Expect massive workloads on these high performing arms – but don’t be surprised if they end up on the DL in the coming seasons.





Ergonomist (CCPE) and Injury Prevention researcher. I like science and baseball - the order depends on the day. Twitter: @DrMikeSonne

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dtpollittmember
6 years ago

This is great stuff, thanks.