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Examining the Effects of the Shift on Kolten Wong’s Stats

MLB: NLCS-St. Louis Cardinals at Washington Nationals Brad Mills-USA TODAY Sports

It is difficult to give Kolten Wong enough praise for his 2019 season. He finished be year with 3.7 WAR, by far his highest single season total. On top of winning a Gold Glove, Wong posted a solid 108 wRC+ and helped the Cardinals fend off the Brewers and the Cubs down the stretch; he hit .290 in the season’s final month. However, despite this year’s success at the plate, there seem to be questions pertaining to the sustainability of Wong’s offensive success.

These questions are well founded, as most of Wong’s expected numbers fell well below his actual numbers. Wong’s .334 wOBA outperformed his .308 xwOBA, which actually hovered right around his career average of .310. His .423 slugging was also well above his .368 xSLG, and his .285 batting average was much better than his .259 xBA. One of the reasons for these disparities is Wong’s average second percentile exit velocity of 83.6 mph and his 7th percentile barrel percentage of 2.5 percent.

An inability to consistently hit the ball hard seems to be a bad sign for the Cardinals second baseman if he wants to replicate these numbers again next season. Wong isn’t necessarily doomed though. One way that Wong creates value at the plate is through strong on-base skills. He is a contact oriented hitter who is able to limit his strikeouts (15.1 K% in 2019) and reach base with walks (8.6 BB% in 2019) and hit by pitches (13 in 2019, 39 since 2017). This helps him to maintain a strong on-base percentage even when he is struggling to hit the ball. Wong posted a .361 OBP this season and a .332 OBP in 2018, which is pretty good when considering his .249 batting average for the span.

Wong’s exit velocity numbers are likely negatively skewed due to the fact that he hit against 232 shifts this season. Against the shift, 57 of his 76 hits went for singles, while 17 of them dropped for doubles. Wong batted .339 against the shift and recorded just an .094 ISO. This is a sign of a change in approach at the plate that could explain why he appeared to struggle to hit the ball hard. When teams shifted against Wong, he focused more on hitting the ball up the middle or to the opposite field, even more so than usual. Wong pulled the ball in 34.1 percent of his plate appearances against the shift, while he pulled the ball nearly 38 percent of the time overall in 2019. Hitters tend to have less power to the opposite field and the middle of the field, so it makes sense that Wong’s ISO would be so low against the shift. Wong’s infield hit percentage also rose significantly against the shift. Overall, in 2019, it was 9.5 percent, but against the shift his IFH% was 14.7 percent. Wong also bunted 24 times and reached base successfully on 11 of those bunts.

An opposite field focus, infield hits, and bunt hits are all things that suppress exit velocity. Wong employs all of these techniques against the shift, which was used against him in over 42% of his plate appearances in 2019. Weak contact can lead to a significant amount of hits against the shift, as Wong demonstrated this season. These weak hits are a necessary part of his success and are likely sustainable over the long term. There will always be large holes in the infield if defenses keep shifting against Wong, so targeting these holes regardless of the quality of contact is not a bad idea.

Some players have found success against the shift by elevating the ball more in order to keep pulling the ball. This is not a bad strategy for a player who has a lot of power, or even moderate power. Nonetheless, this strategy is not likely to work for the 5’9”, 185 pound Kolten Wong. Instead, Wong is likely to be more successful by using his speed (24 stolen bases in 2019) to his advantage.

With such a large percentage of his at bats coming against the shift (42%) it is likely that his expected numbers are not correct. They will punish him or weak contact against the shift that actually has a very good good chance of being a hit. Because of this, Wong should not be expected to regress drastically. Wong still benefited from a .321 BABIP, and there may be some truth to his expected numbers. However, Wong is likely not going to regress as much as might be initially expected. At the very least, he should not be expected to regress back to his career average wRC+ of 96. It is difficult to gauge exactly how much Wong’s lack of power against the shift dragged down his exit velocity and expected numbers. Either way, we shouldn’t be surprised if Wong is able to consistently outperform the metrics.