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(*) RESEARCH: Spring Training stats you can use
Mar 16 2017
Spring Training Stats: Once More, with Meaning!
It is a commonly held belief that spring training stats don’t mean anything, or mean little, with respect to the upcoming season. But in reality, there are a few things that we can glean from March results that will help us plan for the upcoming season. Below we will find for meaning in league-wide home run per flyball rates, and individual stolen base totals.
The League Homerun Surge
As we all well know by now, the HR rate has surged in the last two years. Beginning around the All-Star break in 2015, the HR/FB rate kicked up league wide and threw projections and valuation models into chaos. Recall, the HR/FB rate in recent years:
---Homeruns per Fly Ball---
Year Season 1st Half 2nd Half
===== ====== ======== ========
2011 9.7% 9.0% 10.6%
2012 11.3% 11.2% 11.4%
2013 10.5% 10.8% 10.1%
2014 9.5% 9.8% 9.1%
2015 11.4% 10.7% 12.1%
2016 12.8% 12.9% 12.7%The dramatic increase in home runs changed the baseball landscape. When you can find 20-home run power on the waiver wire, power-only guys have become less valuable, in both fantasy baseball and real baseball. Flyball pitchers also suffer, while groundball pitchers and strikeout artists thrive.
We figured it would be nice to know if we could count on this to continue. Is there was a way to know before the season starts what the homerun landscape would look like this year? We look to spring training data to answer this.
Unfortunately, batted ball data isn’t recorded for spring training. However, mlb.com does have spring stats going back to 2006, and nestled snugly in the second page of stats is “AO”, air outs.
We tabulated the HR/AO in spring training going back to 2006, and compared it to the following season’s HR/FB:
There is a good, though not perfect correlation, with an R2 value of .57. Given that 2015 had a dramatically different 2nd half HR/FB rate, that’s maybe not unexpected. What if we look at the 1st Half HR/FB rate versus spring HR/AO?
The correlation improves, with and R2 of .68. 2015 falls right on the line. So, the spring HR/AO rate gives us a pretty good idea of the HR/FB rate for the upcoming season, particularly for the first half of the season.
Where does that leave us for 2017?
As of March 14, the HR/AO rate in spring training is 13.0%, nearly the same as 2016. So, it appears MLB hasn’t packed away those juiced balls just yet. The HR/FB landscape seems stable for 2017, and fly ball pitchers are particularly vulnerable. Be wary of any projection that regresses pitchers all the way back to 10% HR/FB; 13% is a more likely starting point.
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Stolen Base Surprises
Every year several unexpected sources of stolen bases emerge during the season. We will look at the spring training stolen base leaderboards and see whether historically they could have helped us identify some players to watch.
We identified all players in the top 10 (including ties) in stolen bases for each spring training, 2010-2016. The cutoff is typically 5 or 6 stolen bases.
We tabulated their projected AB and SB, their actual AB and SB, and compared the results to those players NOT in the top-ten. It turns out that relative to projections, players with top-ten spring SB totals and low playing time projections outperformed those who were not in the top ten. Here are the averages by projected playing time bin:
---- Not in the Top Ten ---- --------- In the Top Ten ---------
Proj AB Actual Proj Actual SB Actual Proj Actual SB
Range N AB SB SB Diff N AB SB SB Diff
======= ==== ==== ==== ==== ==== ==== ==== ==== ==== ====
0—100 1563 82 1 2 1 37 128 2 7 5
100—300 1052 162 3 3 0 22 251 11 17 6
300—500 957 338 7 5 -2 19 387 26 22 -4
500—700 918 485 12 9 -3 28 489 30 26 -4So we see that players in the SB leaders and low playing time projections outperform both their projected AB and projected SB in the following season.
Let’s look at it another way, averaging over projected Stolen Base bins. First those not in the spring training top ten:
Not in Top 10
Proj SB Proj Actual SB Proj Actual PT
Range N SB SB Diff AB AB Change
======== ==== ==== ==== ==== ==== ==== =====
0 — 4 3153 1 1 0 186 176 - 5%
5 — 9 636 7 5 -2 388 341 -12%
10 — 19 432 14 10 -4 463 404 -13%
20 — 29 180 23 18 -5 510 434 -15%
30 — 39 61 34 26 -8 539 480 -11%
40 + 28 47 34 -13 556 480 -14%On average, these players didn't meet their projected playing time or SB totals. Now for those in the top ten:
In Top 10
Proj SB Proj Actual SB Proj Actual PT
Range N SB SB Diff AB AB Change
======== ==== ==== ==== ==== ==== ==== =====
0 — 4 39 2 5 +3 50 116 +132%
5 — 9 8 6 15 +9 252 351 + 39%
10 — 19 24 14 19 +5 337 368 + 9%
20 — 29 14 24 22 -2 454 422 - 7%
30 — 39 11 34 26 -8 495 432 - 13%
40 + 10 49 39 -10 502 449 - 11%At the high end, it's still hard to meet those projected AB and SB totals. However, at the lower projected totals, the previous story is confirmed: players among the spring training SB leaders tend to outperform their projections.
Let’s see whether we can use this to find the SB breakouts -- players who unexpectedly put up a 30+ SB season. Here are the 30+ SB seasons from the two groups:
Proj SB 30+ SB Season/Player <= 5 SB Season/Player Range No Top Ten Top 10 No top Ten Top 10 ========= ========== ========== ========== ========== 0 — 4 0% 0% 94% 67% 5 — 9 1% 0% 66% 25% 10 — 19 3% 21% 30% 17% 20 — 29 15% 21% 13% 0% 30 — 39 44% 55% 5% 18% 40 + 61% 70% 0% 10%
The results are clear: for all levels of SB projection, good spring training results correlate with higher SB output during the season. The biggest benefit would seem to come from players projected in the modest 10 - 20 range.
Looking back to last year, this test would have flagged the players below.
Successes:
Player Proj SB Act SB ================= ======= ====== Keon Broxton 6 23 Trea Turner 16 30 Travis Jankowski 14 30 Leonys Martin 18 24 Chris Owings 13 21 Jean Segura 23 33
Whiffs
Player Proj SB Act SB ================= ======= ====== Billy Burns 36 17
Push
Player Proj SB Act SB ==================== ======= ====== Arismendy Alcántara 1 3 César Hernández 19 17 Darin Mastroianni 0 1 Rico Noel 4 5 Shawn O’Malley 3 6 José Peraza 20 21 Joey Rickard 0 4 Domingo Santana 6 2 Chris Tilson 2 0
For 2017, here are the players with 3 or more SB (as of March 14), along with their projected SB totals (the full list can be found on mlb.com).
Player Team Proj AB Proj SB ==================== ==== ======= ======= Aneury Tavarez BAL 0 0 Delino DeShields TEX 152 10 Derek Fisher HOU 30 1 Jacob May CHW 0 0 Ian Miller SEA 0 0 Shawn O’Malley SEA 94 3 Roman Quinn PHI 220 20 Michael Taylor WSH 94 5 Greg Allen CLE 61 3 Jose Altuve HOU 635 25 Rusney Castillo BOS 32 1 Dylan Cozens PHI 0 0 Travis Demeritte ATL 0 0 Chris Denorfia COL 0 0 Jarrod Dyson SEA 409 38 Jacoby Ellsbury NYY 499 17 David Fletcher LAA 0 0 César Hernández PHI 453 17 Jake Marisnick HOU 97 4 Taylor Motter SEA 63 3 Wil Myers SD 582 20 Gerardo Parra COL 292 5 José Peraza CIN 588 38 Tommy Pham STL 215 6 Gregory Polanco PIT 560 21 Ben Revere LAA 359 17 Joey Rickard BAL 93 3 Danny Santana MIN 216 10 Eric Sogard MIL 31 1 Trea Turner WAS 539 41 Eric Young Jr. ANA 32 2
In looking for breakouts, let’s focus on the 10-20 ish projected SB range. These six players are prime candidates for SB upside.
Delino DeShields – He appeared on this list in 2015, when he then went on unexpectedly to produce 25 steals. He is currently penciled in as the fourth OF in Texas, though Profar is not a lock to be productive, and their DH Shin-Soo Choo is often injured.
Roman Quinn – Trapped behind veterans Howie Kendrick, Michael Saunders, and Chris Coglan, he may start in AAA but could force his way into playing time. If he gets called up, pull the trigger quickly.
César Hernández – He attempted 30 steals last year but only succeeded 17 times. Simply improving his success rate would get him into the low 20s. 30 would not be outlandish.
Gregory Polanco – He has been playing in the World Baseball Classic, so his 3 steals are in 5 games. He keeps getting larger (putting on muscle), so it’s a good sign that he’s still stealing bases.
Ben Revere – He averaged 35 steals for 5 years before last year’s H% debacle. All he needs is playing time, and showing that his wheels still work is a good way to earn it.
Danny Santana – He has battled injuries the last few years, including to his hamstring, so it’s encouraging that he’s running now. He may never hit .300 again, but if he can find a way to get on base, there is SB upside.
Finally, the studs: Turner, Altuve, Dyson Peraza. Take note that even though they aren’t going to surprise anyone with their speed, their high spring SB totals are a good sign, correlated with greater likelihood of reaching the projections. This should give you a little more confidence in their upcoming season on draft day, relative to speedsters who aren’t running.
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