Incorporating Sprint Speed into Hitter Projections

One of the keys to fantasy success involves finding when projections can be systematically off. The hard part for fantasy owners is that most of these findings, like pitch velocity, get quickly incorporated into projections. Since it’s difficult to find these discrepancies, I was intrigued when I saw this quote by Mitchel Lichtman (MGL) in an article he wrote:

So, the substantial under-projections seem to occur when a player gains speed but his wOBA remains about the same.

And by substantial, it was a 22 point difference is wOBA. This is a major difference and could point owners to some nice upside plays. I decided to go ahead and dive in.

Two items of note. First, his study was only on a single three-year data sample. We have two three-year sprint speed data samples so the dataset doubled. Second, I’m not a fan of wOBA as a fantasy measure of overall hitting talent. I’d prefer OPS since it’s available on every baseball website and is nearly a perfect proxy for wOBA with an in-season r-square of .99. The conversion is 2.55 points of OPS = 1 point of wOBA.

The first item to get resolved is to recreate the study. Here’s MGL’s statement:

… separated them into 3 groups: One, an increase in speed greater than .5 seconds. Two, a decrease in speed of at least .46 second. Three, all the rest. I also separated each of those groups into 3 sub-groups: One, an increase in context-neutral wOBA of at least 21 points, a decrease of at least 21 points, and all the rest.

I can do the .5 seconds but for the wOBA values, I needed to convert them into OPS which works out to +/- 54 points (2.55*21).

I tried to recreate the analysis after adjusting for the yearly scoring environment. Using historic Steamer projections, here are the results.

Actual minus Projected OPS
OPS Up OPS Same OPS Down
Speed Up .000 .015 .021
Speed Same .002 .000 -.002
Speed Down -.008 .010 -.023

The area MGL noticed (OPS Same, Speed UP) did see its results exceed the projections but not close to the original amount. The original study was at 56 points of OPS (22 wOBA*2.55 OPS/wOBA). These results seem to be a little more in line with my expectations/gut.

To convert OPS to fantasy relevant stats, I’m going back to a previous article where I found how much a change is OPS changes a hitter’s stats. While sprint speed may most likely be linked to a player’s stolen bases, MGL’s study assumed it was a proxy for overall health. I calculated a 10-point OPS change for easy conversion and the original 56-point change (22 wOBA * 2.55 OPS/wOBA) prorated to 600 PA.

Fantasy Stat Changes Based on OPS
Stat 10-point change 56-point change
AVG .0030 .0168
OBP .0033 .0185
SLG .0067 .0375
Runs 0.9 5.1
HR 0.5 2.5
RBI 1.0 5.9

The 56-point difference is what made me excited but the change is barely noticeable at 10-points.

Using the first table, three groups stick out as having their projections and results diverge:

  • Speed up, OPS same
  • Speed up, OPS down
  • Speed down, OPS down

Here are the players going into next season placed in two groups. The hitters who saw their sprint speed increase but OPS stay the same or drop are in the first table. The other table contains those who have both their OPS and sprint speed decline. First, here are the over potential projection overperformers.

Hitters Who Should Outperform Their Projections
Name 2017 OPS 2018 OPS Change 2017 Sprint Speed 2018 Sprint Speed Change
Grandal, Yasmani .767 .815 .049 24.0 24.5 0.5
Kemp, Matt .781 .818 .037 24.9 26.2 1.3
Gonzalez, Carlos .762 .796 .034 26.9 27.5 0.6
Gonzalez, Adrian .642 .672 .030 23.7 24.4 0.7
Smith, Dominic .658 .675 .017 25.4 26.3 0.9
Heyward, Jason .715 .731 .016 27.1 27.6 0.5
Freitas, David .588 .589 .001 24.6 25.1 0.5
Cuthbert, Cheslor .596 .583 -.013 25.6 26.9 1.3
Segura, Jean .776 .755 -.021 27.1 27.9 0.8
Turner, Justin .945 .924 -.021 25.5 26.6 1.1
Luplow, Jordan .660 .631 -.030 28.2 28.7 0.5
Rosario, Eddie .836 .803 -.033 27.5 28.1 0.6
Shaw, Travis .862 .825 -.037 25.7 26.7 1.0
Martinez, Victor .697 .651 -.046 22.6 23.2 0.6
Rua, Ryan .627 .580 -.047 27.8 28.6 0.8
Inciarte, Ender .759 .705 -.054 27.2 27.9 0.7
Lobaton, Jose .525 .470 -.055 23.7 24.7 1.0
Moustakas, Mike .835 .774 -.061 24.0 25.7 1.7
Gurriel, Yuli .817 .751 -.066 26.9 27.6 0.7
Calhoun, Willie .677 .602 -.075 25.4 26.5 1.1
Chirinos, Robinson .866 .757 -.109 24.7 25.3 0.6
Gimenez, Chris .731 .621 -.110 24.9 25.5 0.6
Joseph, Caleb .700 .575 -.125 25.9 26.4 0.5
Orlando, Paulo .527 .394 -.133 28.4 29.1 0.7
Dyson, Jarrod .674 .539 -.134 28.2 29.0 0.8
Beltre, Adrian .915 .763 -.153 24.3 24.9 0.6
La Stella, Tommy .861 .672 -.189 26.2 26.7 0.5
Votto, Joey 1.032 .837 -.195 24.9 25.4 0.5
Olson, Matt 1.003 .788 -.214 24.3 25.9 1.6
Cozart, Zack .933 .658 -.275 26.0 26.6 0.6
Tauchman, Mike .640 .319 -.321 28.4 28.9 0.5

And now those who should, on average, not reach their projected OPS.

Hitters Who Should Underperform Their Projections
Name 2017 OPS 2018 OPS Change 2017 Sprint Speed 2018 Sprint Speed Change
Rasmus, Colby .896 .426 -.470 27.2 25.8 -1.4
Villanueva, Christian 1.094 .750 -.344 26.7 25.7 -1.0
Fowler, Dexter .851 .576 -.275 28.1 27.4 -0.7
Cowart, Kaleb .695 .451 -.245 27.4 26.8 -0.6
Avila, Alex .834 .603 -.230 25.0 23.8 -1.2
Sucre, Jesus .699 .500 -.198 24.3 22.9 -1.4
Vazquez, Christian .735 .540 -.194 25.8 25.3 -0.5
Centeno, Juan .632 .454 -.177 25.7 24.7 -1.0
Hosmer, Eric .882 .720 -.162 27.1 26.3 -0.8
Bruce, Jay .832 .680 -.152 26.3 25.5 -0.8
McCann, James .733 .581 -.152 26.7 25.9 -0.8
Donaldson, Josh .944 .801 -.143 26.4 25.4 -1.0
Blackmon, Charlie 1.000 .860 -.140 28.2 27.6 -0.6
Kelly, Carson .457 .319 -.138 25.8 24.7 -1.1
Murphy, Daniel .928 .790 -.137 26.2 25.5 -0.7
Iannetta, Chris .865 .730 -.135 25.8 25.3 -0.5
Souza Jr., Steven .810 .678 -.132 28.9 28.1 -0.8
Panik, Joe .768 .639 -.129 26.1 25.6 -0.5
Alonso, Yonder .866 .738 -.128 24.6 23.3 -1.3
Telis, Tomas .625 .499 -.126 26.3 25.6 -0.7
Flowers, Tyler .823 .700 -.123 25.8 25.3 -0.5
Beckham, Tim .782 .661 -.121 28.1 27.2 -0.9
Harrison, Josh .771 .656 -.115 27.6 27.1 -0.5
Bryant, Kris .946 .834 -.112 28.9 28.0 -0.9
Mancini, Trey .826 .715 -.111 27.5 27.0 -0.5
Seager, Corey .854 .744 -.110 26.8 26.1 -0.7
Castillo, Welington .813 .710 -.103 24.9 23.7 -1.2
Young, Chris .709 .615 -.094 27.6 27.1 -0.5
Rojas, Miguel .736 .643 -.092 27.0 26.5 -0.5
Devers, Rafael .819 .731 -.088 28.0 27.3 -0.7
Duda, Lucas .818 .731 -.087 25.6 24.9 -0.7
Happ, Ian .842 .761 -.081 28.8 27.7 -1.1
Zimmer, Bradley .692 .611 -.081 30.0 29.4 -0.6
Frazier, Todd .772 .693 -.079 26.5 25.7 -0.8
Perez, Salvador .792 .713 -.079 25.6 25.1 -0.5
Martinez, Jose .897 .821 -.077 27.6 26.5 -1.1
Cruz, Nelson .924 .850 -.073 25.5 24.9 -0.6
Travis, Devon .729 .656 -.073 27.4 26.9 -0.5
Hechavarria, Adeiny .695 .624 -.071 28.0 27.0 -1.0
Belt, Brandon .823 .756 -.068 26.7 25.9 -0.8
Healy, Ryon .754 .688 -.065 26.6 26.0 -0.6
Russell, Addison .722 .657 -.064 28.2 27.5 -0.7
Williams, Nick .811 .749 -.062 29.1 28.4 -0.7

In all fairness, the second list is more interesting. Some of the drops can be explained but injury (e.g. Donaldson and Seager) but others might be players heading down like Hosmer and Blackmon.

Sprint speed and now home-to-first times (bottom of the page) can help owners get another peek into a player’s profile. Just this weekend, I found out and read a report stating a link between the sprint speed and health of athletes. While the link seems obvious, it hadn’t occurred to me to add a speed variable to my injury analysis.

I think changes in a player’s sprint speed can help to find changes in talent. The problem, for now, is incorporating those changes with such a small data sample. I expect major advances in this area but to begin with, some dead ends will be found. Hopefully, I was able to push the research foward a little.



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Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won three FSWA Awards including on for his MASH series. In his first two seasons in Tout Wars, he's won the H2H league and mixed auction league. Follow him on Twitter @jeffwzimmerman.

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chrisjacoby
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chrisjacoby

Did you consider controlling for age, e.g. over 30/ under 30. Seems there are a chunk of players on both lists that are in the over 30 camp.