RESEARCH: Spring Training stats you can use

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.


Take charge of your league in 2017 with a BaseballHQ.com subscription that unlocks articles like these all season long. Winning. Fantasy baseball. Insight.


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     -4

So 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 Alcantara       1          3
Cesar Hernandez          19         17
Darin Mastroianni         0          1
Rico Noel                 4          5
Shawn O’Malley            3          6
Jose 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
Cesar Hernandez        PHI     453       17
Jake Marisnick         HOU      97        4
Taylor Motter          SEA      63        3
Wil Myers              SD      582       20
Gerardo Parra          COL     292        5
Jose 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.

Cesar Hernandez – 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.

 


Click here to subscribe

  For more information about the terms used in this article, see our Glossary Primer.