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# 2017 Statcast Data: Tomas and Goldy

Let’s mix things up and take a look at some of our hitters so far into 2017!

Today, we’ll take a break from going over the stats and do some analysis. Luckily for us, the first batch of 2017 Statcast data was uploaded over the weekend and we can start to see how some of our hitters are doing!

The main thing we can use Statcast data for, at least right now, is appropriately measuring power. Statcast itself is mostly raw, observable data (things like exit velocity) but it also has some metrics that have been slowly added. One of these new metrics is “barrels” which is a tool used to try and find “well-hit” balls. To do this, the exit velocity and launch angles of all balls in play was analyzed and any combination of the two components that netted a BABIP of .500 or higher and a SLG of 1.500 or higher was defined as a “barrel”. This means that a “barrel” would generate a hit at least 50% of the time and averaged at least one extra base on each hit. Currently, a barrel starts with an exit velocity of 98 MPH or greater and a launch angle between 28 and 30 degrees; this launch angle then expands as the exit velocity increases. See HERE for a visual to help understand what I’m trying to describe here.

The real benefit of this Statcast data is that it has helped us to build better calculators, particularly on our power calculators, to help determine the validity of a player’s power. We’re going to use xISO and xHR/FB%, both of which have been updated to include Statcast data, to help in our analysis today. The main purpose for these calculators is for us to estimate how “real” a player’s stat is. So, if a player has an xISO of .200 but is currently sitting on a .400 ISO, we should expect the .400 ISO to drop. This does not mean that the player will have a sub .200 ISO such that their “final” ISO ends up at .200; rather, this suggests that the player is more likely to have about a .200 ISO going forward.

The current model of xISO has an R^2 of 0.8156.

The current model of xHR/FB% has an R^2 of 0.6815.

These are both fantastically high R^2 values. What R^2 (pronounced “r squared”) essentially tells you is the amount of variation in your data sample that is captured by your formula. For example, using the xISO model, you can calculate approximiately 81.56% of a player’s true ISO talent with just the inputs of FB%, GB%, and Barrels/PA. The remaining ~18.5% of a player’s true ISO is going to come from other variables that are not included in those three inputs.

We’re still on the small sample size side of things, but now that we’re at 30+ balls in play, we’re getting closer to having pretty reasonable estimations. Small samples in these cases means that a player’s ISO and xISO (or HR/FB% and xHR/FB%) will still have decent fluctuations, but these fluctuations will get smaller and smaller as the sample size increases.

## Yasmany Tomas’s Power is Real

There has been a lot of discussion regarding Yasmany Tomas. The overall perception of Tomas, at least online, is generally very negative. His OF defense is bad and continues to be bad. He struggles with his baserunning. And he put up only 88 and 109 wRC+ in his first two seasons in the MLB when he was supposed to be a premier hitter.

However, there was also a tale of two Tomas’s in 2016. First half Tomas had an 88 wRC+ while second half Tomas had a 133 wRC+ with 18 HR in only 259 PA. Most Tomas critics chalked up his second-half improvement to a “lucky” home run barrage and expected regression in 2017.

However, I was the opposite - I was one of the few believers in Tomas’s power because of changes he had made (and had been continually making) to his flyball rates (FB%). Tomas clearly has power but in order to get to that power, one has to hit flyballs. Here is a rolling average of Tomas’s FB% since he came to the MLB:

Tomas posted a second-half FB% of 33.0% last season and I asserted that if he was able to maintain that going forward, he would be about a ~120ish wRC+/OPS+ and .220 ISO type of player with room to go higher. Currently, Tomas sits at 145 wRC+, .303 ISO, and 34.8% FB%. What does Statcast have to say about Tomas?

### Tomas Statcast April

Metric 2016 2017
Metric 2016 2017
Avg EV (MPH) 91.4 91
Avg FB/LD EV (MPH) 95.1 96.9
Brls/BBE 10.60% 15.20%
Brls/PA 7.46% 10.14%

The overall average exit velocity is down slightly from last year, but beyond that, Tomas is hitting flyballs harder and making better contact (barrels) than last year. Combine this with his increasing (so far) FB% and it’s clear as day to see that his second-half power has carried over. What do xISO and xHR/FB% have to say?

ISO: .303

xISO: .250

HR/FB%: 25.0%

xHR/FB%: 22.9%

A bit expectedly, the Statcast data is calling for regression to Tomas. However, calling for a .250 ISO and ~23% HR/FB% going forward is still very, very good and I would say vastly improved over his expectations prior to the season. At a .250 ISO, Tomas is going to be in the 130+ range for wRC+/OPS+ and we don’t know where his improvements will end, if they haven’t already.

The concerns about his defense and baserunning aren’t going to go away and Tomas should be a 1B or DH from a value perspective. But as a hitter, Tomas is looking really good and the data backs most of it up. If Tomas keeps hitting like this, he will be worth at least the remaining value of his contract and would be a possible net positive if he was used as a 1B or a DH. Tomas could be the trade bait that I was calling for this offseason.

# Goldy is Back

Another huge concern for this team was that Paul Goldschmidt’s production had mysteriously slipped since around mid-season 2015. From July 1, 2015 to the end of 2016, here are some of Goldy’s numbers:

### Goldy’s Slump

Goldschmidt 2016
Goldschmidt 2016
wRC+ 135
ISO 0.199
FB% 30.30%
IFFB% 12.80%
HR/FB% 19.00%
Hard% 38.20%
Hard% on FB 45.10%

(I made an error in the table: second column is for July 1, 2015 - 2016, not just 2016)

Goldy’s wRC+ took a significant drop over this time and it was all related to his power. He still posted his excellent on-base percentage, but a .199 ISO was lacking compared to the .240-.250 marks he had put up in the previous three seasons. And looking at the batted ball data, there were big drops to his FB%, Hard%, and Hard% on FBs and a big jump in his IFFB%.

However, 2017 looks much different for Goldy, even though the numbers (and his 130 wRC+) don’t currently reflect it. Let’s now compare 2016 and 2017 data, including Statcast info:

### Goldy 2016 vs 2017

Goldschmidt 2016 2017
Goldschmidt 2016 2017
wRC+ 134 131
ISO 0.192 0.2
FB% 28.80% 37.00%
IFFB% 14.30% 5.00%
HR/FB% 19.00% 15.00%
Hard% 37.50% 48.10%
Hard% on FB 44.40% 55.00%
Avg EV (MPH) 92.4 92.3
Avg EV LD/FB (MPH) 95 97.4
Brls/BBE 8.00% 14.80%
Brls/PA 5.00% 9.10%

Goldy’s data is improved pretty much across the board except that it isn’t seen in his wRC+ and ISO. He’s hitting more flyballs, hitting the ball harder, and getting better launch angles (seen in more barrels/BBE and lower IFFB%). What do xISO and xHR/FB% say?

ISO: .200

xISO: .233

HR/FB%: 15.0%

xHR/FB%: 21.5%

The calculations are both predicting some significant positive regression for Goldy’s power. The .233 ISO is much closer to prime Goldy’s numbers (though a tad lower than the .249 he posted) and the 21.5% HR/FB% is right in line with them.

At first glance for 2017, it would look like 2017 Goldy is in the same slump he’d been in the previous 1.5 years. But the batted ball information paints a much different story. So far, it looks like Goldy has been rather unlucky, which perhaps can be seen in his .294 BABIP (.354 career). Goldy’s power may have already peaked, but if he can get his power back to a close level (~.233 ISO) with his improved on-base skills, we might yet see Goldy break 160 wRC+ this year.