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Digging Deep – Buy low Hitters through April

Digging DeepWe’ve gathered over a full month of data and some of the underlying metrics are starting to become more “stable” – by which we mean we can make more confident conclusions about whose performance this year is ”real”. The strikeout rate is one of the quickest hitting characteristics to stabilize; whereas batted ball metrics such as Line Drive rate take far longer to become “reliable”. Therefore, StatCast data – which focuses on batted ball data – although helpful to try to find early diamonds-in-the-rough shouldn’t be the primary source for finding breakouts. In fact, actual results data provide the best early signals that a hitter has taken a substantive step forward or backward

Therefore, to find Buy Low and sell high players, or what we like to call the Hot Rods and Lemons, instead of using the StatCast data to peek at what’s under the hood, we will start using the actual defense-independent results to evaluate whether the hitter has changed their profile from last season. This is not to say that StatCast is not useful at this point in the season. To the contrary, it helps us validate some of the signals we will see from the results data.

The underlying data that we decided to examine were the following rates accumulated by each batter thus far in 2019:

  • Walk rate (BB%)
  • Strikeout rate (K%)
  • Groundball rate (GB%)
  • Hard hit rate (Hard%)
  • Swinging Strike rate (SwStrk%) – to help validate the Strikeout rate

In order to find true sleepers, we restricted the search to Hitters who have accumulated ‘below average’ value so far this year in 2019. In other words, we calculated each hitter’s cumulative 2019 roto performance (BA, not OBP), compared it to the rest of the league and only reviewed those who are produced as a below average hitter. We then looked at which hitters have the largest difference in their hitting profile between 2018 and this year (with the groundball rate being weighted less than the others because (a) it is less important to overall production and (b) it takes more Balls In Play before it becomes reliable than one month of the season; ie is not stable enough to be considered truly reliable).

The following hitters were identified as being below average producers this year but whose hitting profile has actually been better than last year. Therefore, they are believed to be the most likely to provide above average hitting performance for the rest of the season (provided they get the necessary plate appearances).

Lucas Duda, Kansas City Royals

Statistic 2019 (56 PAs) 2018 Difference*
BB% 16.1% 7.6% +8.5%
K% 23.2% 27.8% +4.6%
GB% 23.5% 28.8% +5.3%
Hard% 41.2% 38.4% +2.8%
SwStrk% 11.2% 13.3% +2.1%

*The difference is considered “positive” when it is “better” in 2019 than in 2018. A higher BB and Hard Hit rate is better; a lower K and GB rate is better. Therefore a K rate of 10% in 2019 (compared to 15% in 2018) will be considered a ‘difference’ of +5%. Conversely, a BB rate of 10% in 2019 (compared to 15% in 2018) will be considered a ‘difference’ of -5%. Also, the ‘difference’ is just the absolute difference in the percentages.

Lucas Duda? Really? The guy who is hitting .174 with 2 HR, 8 RBI’s and 3 Runs? Yup. He has actually improved his contact rate, hit the ball harder, hit the ball in the air more, and is taking more walks (double his rate from last year). He is currently battling a back issue (missing the last 3 games) but I am quite confident you can find him on the waiver wire (or at the very least be able to pry him from a frustrated owner) quite easily. It might be hard to pull the trigger, but provided that he gets 500 PAs for the rest of the season, he should still be a top 30 Corner Infielder.

Kendrys Morales, Oakland Athletics

Statistic 2019 (76 PAs) 2018 Difference*
BB% 11.8% 10.6% +1.2%
K% 13.2% 20.2% +7.0%
GB% 45.5% 45.8% +0.3%
Hard% 43.6% 40.6% +3.0%
SwStrk% 5.4% 11.4% +6.0%

Look! It’s another poor defensive 1B/DH who has made improvements across the board from their 2018 campaign. Again, it won’t take much to improve on his 2019 thus far –  .172 BA, 1 HR, 4 RBI and 5 Runs – but don’t think that this is just evidence of his age decline: his underlying numbers actually suggest that he should be performing better than how he did in 2018 (when he put up a 108 wRC+). Taking a peek at his StatCast numbers and we see that his xwOBA is 0.381 (which is actually a 60-grade xwOBA). Provided he gets the playing time, look for him to hit around .250 (.320 OBP) with around 20 HRs over his next 500 plate appearances.

Mike Zunino, Tampa Bay Rays</h2>

Statistic 2019 (64 PAs) 2018 Difference*
BB% 4.7% 5.9% -1.2%
K% 21.9% 37.0% +15.1% (!)
GB% 31.9% 37.3% +5.4%
Hard% 46.8% 39.6% +7.2%
SwStrk% 14.0% 17.5% +3.5%

I’m not sure what the Rays have done to help the former highly- touted Mariner catching prospect, but it seems to be working thus far, albeit with relatively modest actual results so far. However, the 28-year-old backstop – who has a career K rate of 34% has significantly reduced his strikeouts to a respectable 22% (which is also supported by his improved SwStrk rate and contact rate). Not only that but he is making harder contact this year whilst lofting it into the air more. Interestingly trivia: his maximum exit velocity thus far this year (116.1 mph) has only been exceeded by Pete Alonso, Aaron Judge, Kyle Schwarber, Mike Trout and Christian Yelich. Not even Joey Gallo has reached 116 mph this year (yet).

Even if Zunino doesn’t hit his StatCast xBA of .252, and “only” hits around .240, paired with his 15+ HRs he should hit the rest of the season, and you have a potential top 10 catcher. I’ve already picked him up in my home league.

Hitters to Avoid (Lemons)

The following hitters have been producing above league average so far this year but their hitting profile has actually degraded compared to last year. Therefore, they are believed to be the most likely to provide below average hitting performance for the rest of the season and should be unloaded if you are able to get 100 cents on the dollar.

Lorenzo Cain, Milwaukee Brewers

Statistic 2019 (117 PAs) 2018 Difference*
BB% 7.7% 11.6% -3.9%
K% 17.9% 15.0% -2.9%
GB% 47.1% 54.6% +7.5%
Hard% 25.9% 38.3% -12.4%
SwStrk% 9.3% 6.9% -2.4%

Oh no, not Lorenzo Cain! Although he is hitting an un-Cain-esque .267, he still has 19 Runs for the high-octane Brewer offense (paired with 3 HRs and 3 SBs). That seems quite good. But I suspect that the hype of Christian Yelich’s offensive performance has obscured the fact that Cain has some significant concerns under the hood. His BB rate is significantly down, his K rate (and Swinging Strike rate) are significantly up, and he is not hitting the ball hard at all. To help illustrate this more clearly, take a look at his 10 game-rolling-average rate going back to 2018 (below): he has not had a lower hard-hit rate, lower BB rate or higher K rate than he does right now.

Lorenzo Cain.png

He does still have an above league average strikeout and contact rate – and he has plumbed these depths before in previous years to 2018 – but when a 33-year-old batter suddenly starts hitting below league average (wRC+ of 98), one can’t help but be concerned. Because he will be hitting near the top of the Milwaukee lineup, he will continue to accumulate numbers (especially Runs) but he likely won’t put up top 20 outfielder numbers (despite being taken as the 19th outfielder off the board in the pre-season). If you can trade Lorenzo Cain to someone who feels his year thus far is just a blip, I would strongly consider it.

Max Muncy, Los Angeles Dodgers

Statistic 2019 (94 PAs) 2018 Difference*
BB% 13.8% 16.6% -2.8%
K% 30.9% 27.2% -3.7%
GB% 36.5% 34.5% -2.0%
Hard% 46.2% 47.0% -0.8%
SwStrk% 10.2% 10.0% -0.2%

Last year’s fantasy darling hasn’t been able to find the same footing that he found last year. Although a .266 BA with 4 HRs, 14 RBIs, and 9 Runs is nothing to sneeze at, most fantasy owners are waiting for him to heat up to get back to the 30 HR pace he achieved last year and they expect again this year. Unfortunately, he has taken a step backward in all of the meaningful metrics. Looking at StatCast too and it’s not much more optimistic as his average exit velocity this year is 88.7 mph (league average) whereas last year it was 90.1 mph and they also “expect” (from his batted ball data) an xBA of .212 (likely due to his .327 BABIP this year, compared to .299 last year – a 10% inflation). It’s still early, and he hasn’t taken that much of a step backward from last year’s numbers, but again, if someone is trying to get you to trade him and is willing to pay close to last year’s prices, I would think about it.

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