January 22, 2022

Statistically Speaking: Free Swingers or Patient Producers?

As a team that employs one of the more balanced offenses in the National League, it’s no big surprise that the Washington Nationals sit atop myriad offensive categories, on the team and individual levels. Currently in third place behind a pair of NL West foes—the Colorado Rockies and Los Angeles Dodgers—in runs scored per game (at 4.24), the Nats runs have come from a number of expected and surprising sources, up and down the lineup card.

Whether your statistic of choice is of a more traditional flavor (4th in home runs, 5th in runs batted in) or something a little more nuanced (4th in wOBA and OPS), the Nats are more than likely in the top five of said league offensive category.

With a powerful offense comes powerful swings; however, these swings may not necessarily always make contact and for the Nats, this unfortunately can often be the case. Looking at their team strikeout and walk rates, the Nats rank sixth (21.1%) and fifth (8.2%) in the NL, respectively, which adds some context to their general offensive numbers, but also leads to another question as to what kind of hitters they are as a unit.

Thanks to the wonders of PITCHf/x data (and FanGraphs!), we have access to more granular data of how often and how successful a swing can be for a given player, in the form of swing and contact rates on pitches in and out of the strike zone, as well as swinging strike rates; these are known categorically as plate discipline stats. With these numbers, we can better appreciate whether the Nats are a team of free swingers or a collection of hitters with a more refined approach to hitting, working counts and pitchers to their advantage.

First, let’s look at those numbers; for our purposes, only Nats hitters with at least 100 PA are considered and NL averages and standard deviations for each stat (also for player with at last 100 PA) are also included:

Name O-Swing% Z-Swing% Swing% O-Contact% Z-Contact% Contact% SwStr%
Nate McLouth 19.60% 55.80% 36.80% 64.10% 93.30% 85.10% 5.40%
Anthony Rendon 23.60% 61.90% 41.40% 73.60% 93.30% 87.30% 5.20%
Jayson Werth 24.30% 54.30% 37.50% 69.00% 90.80% 83.00% 6.30%
Denard Span 24.50% 61.80% 42.80% 82.70% 96.00% 92.10% 3.40%
Adam LaRoche 24.90% 63.90% 40.70% 65.30% 88.90% 80.30% 7.90%
Ryan Zimmerman 28.80% 53.10% 39.50% 69.10% 92.40% 82.90% 6.70%
Jose Lobaton 31.30% 74.00% 50.00% 62.10% 82.50% 75.30% 11.90%
Asdrubal Cabrera 34.30% 77.90% 51.70% 70.80% 90.90% 82.90% 8.70%
Ian Desmond 34.70% 68.50% 50.10% 54.00% 83.60% 72.40% 13.70%
Bryce Harper 36.00% 75.80% 51.40% 58.90% 83.10% 72.80% 13.70%
Kevin Frandsen 36.60% 69.50% 52.80% 70.70% 89.80% 83.00% 8.90%
Danny Espinosa 37.70% 70.80% 51.70% 52.00% 74.90% 65.30% 17.50%
Wilson Ramos 38.60% 81.40% 58.00% 66.20% 87.90% 80.00% 11.30%
NL Average 31.80% 66.10% 47.20% 65.10% 86.90% 78.80% 9.80%
NL St Dev 0.0582 0.0630 0.0503 0.0923 0.0488 0.0618 0.0335

As far as categories, those with an ‘O-‘ prefix denote swings/contact outside of the strike zone, while ‘Z-‘ denotes the same things, just inside the strike zone. Swing% and Contact% are overall rates for each statistic, and SwStr% is shorthand for the aforementioned swinging strike rate.

There’s a lot of information to digest here, but overall, the trend would be for free swingers to swing more in general across all categories and will more than likely have a higher swinging strike rate. Of course, contact rates give further context as to whether the swings are fruitful; more on that in a moment.

A nice way to whittle down the data without losing too much of the detail in the numbers—especially each hitter’s differences against NL averages—is to apply a z-score to each; let’s do that now, with the formula for calculating a z-score being:

z = (X – μ) / σ

where z is the z-score, X is the value of the element, μ is the mean, and σ is the standard deviation.

Let’s first take a look at swing stats; here, the more positive a z-score, the more free swinging a player is, compared to NL averages. A total z-score (just all z-scores added up) is also provided:

Name zO-Swing zZ-Swing zSwing zSwStr zTotal
Wilson Ramos 1.168 2.429 2.147 0.448 6.192
Danny Espinosa 1.013 0.746 0.894 2.300 4.954
Bryce Harper 0.721 1.540 0.835 1.165 4.261
Asdrubal Cabrera 0.429 1.874 0.894 -0.329 2.869
Ian Desmond 0.498 0.381 0.576 1.165 2.620
Jose Lobaton -0.086 1.254 0.557 0.627 2.352
Kevin Frandsen 0.824 0.540 1.113 -0.269 2.208
Adam LaRoche -1.185 -0.349 -1.292 -0.568 -3.394
Anthony Rendon -1.408 -0.667 -1.153 -1.374 -4.602
Denard Span -1.254 -0.683 -0.875 -1.912 -4.723
Ryan Zimmerman -0.515 -2.064 -1.530 -0.926 -5.036
Jayson Werth -1.288 -1.874 -1.928 -1.046 -6.135
Nate McLouth -2.095 -1.635 -2.067 -1.314 -7.112

Overall, there aren’t too many huge surprises here, with the likes of Wilson Ramos, Danny Espinosa, Bryce Harper, and Ian Desmond—all notorious in their aggressive approaches—leading the free swinger pack, while Jayson Werth and Ryan Zimmerman show a more patient hitting approach.

One interesting quirk comes from Asdrubal Cabrera, who shows a big tendency to swing, but fares well in not swinging and missing (zSwStr). Overall, it’s an interesting spread, with the Nats in general showing a large swing to one end of the swinging spectrum or another, with no players showing an average (scores close to zero) approach.

Now, let’s look at contact rates, with the same caveats in mind, adding the notion that if a big swinger makes a lot of contact, the pitfalls of a ‘grip it and rip it’ approach could be defrayed somewhat, due to increased production (potentially):

Name zO-Contact zZ-Contact zContact zTotal
Denard Span 1.908 1.863 2.153 5.925
Anthony Rendon 0.921 1.311 1.376 3.608
Ryan Zimmerman 0.434 1.126 0.664 2.224
Nate McLouth -0.108 1.311 1.020 2.222
Asdrubal Cabrera 0.618 0.819 0.664 2.101
Jayson Werth 0.423 0.799 0.680 1.901
Kevin Frandsen 0.607 0.594 0.680 1.881
Adam LaRoche 0.022 0.410 0.243 0.674
Wilson Ramos 0.119 0.205 0.194 0.518
Jose Lobaton -0.325 -0.901 -0.567 -1.793
Bryce Harper -0.672 -0.778 -0.971 -2.422
Ian Desmond -1.203 -0.676 -1.036 -2.915
Danny Espinosa -1.420 -2.457 -2.186 -6.063

There are a couple of top-bottom swaps in between this and the previous table—most egregiously, Danny Espinosa—indicative of a lots of swings…and a lot of misses. Not surprisingly, the top of the order duo of Denard Span and Anthony Rendon sit atop the contact table. Super sub Kevin Frandsen also appears to make the most of his time at the plate, putting the ball in play at a higher than average rate, something that had led to manager Matt Williams using him in a number of high leverage, late game situations.

While these trends don’t always amount to much over the length of the regular season, they could portend to troubles in the playoffs for individual players, where the need to expose a hitter’s weakness and use it for a competitive advantage is of the essence in the scant five- and seven-game match ups of the postseason. Playing to a hitter’s impatience at the plate or their inability to lay off certain pitches in certain areas of the strike zone are what can make a fantastic regular season become moot after three games in October.

For the Nats, there is certainly potential for these hypotheticals to become reality; however, given the balance seen in their overall offensive prowess is also reflected in these plate discipline data, the potential for the patient hitters to counter the free swingers of the group remains large, much like the Nats chances of a long postseason.

All data courtesy of FanGraphs and current as of September 23rd. 

About Stuart Wallace

Stuart Wallace is a Contributor to District Sports Page. A neuroscientist by day, the Nevada native also moonlights as an Associate Managing Editor for Beyond the Box Score, stats intern at Baseball Prospectus, and a contributor at Camden Depot. A former pitcher, his brief career is sadly highlighted by giving up a lot of home runs to former National Johnny Estrada. You can follow Stu on Twitter @TClippardsSpecs.

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