Speedsters and the Issue of Playing Time

Playing time can make or break a baseball player’s fantasy value. An elite player may not finish above replacement level if he suffers an injury and plays only half the season, and a lackluster player could finish above replacement level simply by playing every single day. This is all intuitive, and the fantasy community generally approaches these kinds of things rationally. In other words, most players are appropriately valued, outside of the market inefficiencies that inevitably warp player values.

One-dimensional speedsters — dudes who steal a bunch of bases and do little else — are much harder to peg. Their value is tied up primarily in one category, as stolen bases (SBs) do not directly correlate with other categories the way home runs would with runs and RBI, for example. The issue becomes all the more confounding when one considers the contemporaneous scarcity of SBs relative to home runs. There’s more to value than just SBs and plate appearances (PAs), but the fact of the matter is the two statistics by themselves correlate very strongly with a player’s end-of-season (EOS) value (which, here, are informed by Razzball’s Player Rater).

In the last five years, baseball has seen 75 player-seasons of 30-plus SBs — 15 steals a year on average, a trend that didn’t fundamentally change in 2016 (although that doesn’t mean SBs aren’t scarce). A simple linear regression of SBs and PAs, the latter of which serves as a proxy for other counting stats such as runs and RBI, against EOS value produces a remarkable 0.71 adjusted R²:

EOS = 706.787 — 2.771*SB — 0.835*PA

It’s not an especially rigorous model, and the sample size is especially small, but there still exists a strong correlation, the likes of which can be used to better inform us about the value of base-stealers. Using FanGraphs’ Depth Charts projections, which rely on Steamer projections and staff-allocated playing time, I identified a baker’s dozen worth of “one-dimensional” speedsters and calculated their expected EOS values based on their projected SBs and PAs:

Before you get all up in arms: Trea Turner and Travis Jankowski are obviously not equals. Turner and Jonathan Villar have demonstrated non-zero power. So, too, has Eduardo Nunez and Keon Broxton, and maybe Manuel Margot will end up with double-digit pop one day. Also, Turner appears to have a plus hit tool that should play up his batting average. (The verdict is still out on if he can actually maintain a high batting average on balls in play [BABIP], but this is really not a discussion I want to have right now.) Ultimately, the point is all of these hitters generate most of their value through their speed. In a vacuum, it’s evident we over- and under-value certain players.

The EOS-ADP column indicates the difference in a hitter’s National Fantasy Baseball Championship average draft position (NFBC ADP) and his expected EOS value. Minus is good, plus is bad.

Underrated

Alas, Jankowski may be baseball’s most underrated speedster. I don’t think he will record 630 PAs — competing with Margot, Hunter Renfroe and my boy Alex Dickerson, he could very well end up the odd man out — but given his SB frequency, he would only need to record 419 PAs (and only 25 SBs!) to pay off his draft price. It’s a very attainable playing time threshold, given the Padres will be bad and injuries happen. Reiterating the caveat: this regression considers nothing else of a player’s tools, and Jankowski doesn’t have much else to tout. Still, no matter your take, he is vastly underrated heading into 2017.

Speaking of Margot, he isn’t necessarily guaranteed playing time, either. The San Diego outfield could be a revolving door of hot hands. But, similarly to his teammate, he would need to record only 483 PAs and roughly 21 SBs to break even. Given he’s part of the Padres’ future, I wouldn’t be surprised to see him surpass those marks.

Frankly, I expected Tim Anderson to be overrated. But if he actually plays second base full-time for the White Sox, anything more than his projected 21 SBs is gravy. It just seems like folks are expected even more speed from him, but he suddenly stopped running after his 2015 Double-A stint, so I don’t really know what to think.

I’m suddenly intrigued by Raul Mondesi, Jr. Brandon Warne now manages the American League Central depth charts, so I trust that he has his finger on the pulse of those teams (especially the Minnesota Twins). Mondesi is projected for far more playing time than I expected of him in 2017, and he would only need to play about half the season to pay off his ADP.

Overrated

By this measure, Turner and Villar are both overrated. And I think that’s true, to an extent. But, again, this measure overlooks their other merits — namely, modest power and anywhere from above-average to elite batting average. I think what’s more interesting is Steamer projects more SBs and less PAs for Villar, and I don’t see any reason why he wouldn’t play a full season the same way Turner would. Give Villar another 30 to 40 PAs and he’s already expected to pay off a bit better than Turner.

*Ironically, I moderate the National League Central depth charts, so I have no one to blame but myself for his bearish playing time. But I’m generally more bearish with my playing time estimates for all players, not just Villar.

Billy Hamilton’s ADP basically reflects an expectation of 62 SBs and and 581 PAs — something I think a lot of folks who draft him are hoping for. If he can turn back the clock to 2014 regarding his playing time, he’s gold. But that’s a big “if.”

Mallex Smith is a bit overrated here — his lack of playing time projects him to fall outside the top 400 EOS. But you have to dream on his upside: Steamer projects him to be every bit as speedy as Villar. (I’m talking exactly as speedy: 43 SBs per 560 PAs, just like Villar.) And Smith also has a bit of pop. He’s buried on the Rays’ depth chart, but any injury to Kevin Kiermaier, Colby Rasmus, Steven Souza Jr. or Corey Dickerson could open the door for him to more playing time than just spelling the starters on rest days.

Conclusions

For the thousandth time, caveats abound for this analysis. Namely, it overlooks literally everything but SBs (although PAs account for runs and RBI by proxy). That’s a big deal. But when it comes down to it, a limited regression analysis demonstrates that PAs and SBs alone correlate very strongly with EOS value. You can adjust your own mental calculus for certain players accordingly, but this methodology has at least revealed to us some underrated speedsters to target later in your drafts — and maybe some elite players about whom you should maybe be bearish.

For reference, here are each player’s expected SBs and PAs in order to break even on his ADP: