Kolten Wong’s bad day

If you haven’t heard, Kolten Wong didn’t have the best night in the Cardinals 7-5 loss to the Brewers. He made an error to start the tenth inning, mishandling a line drive, and though he still had time to get the out by knocking it down, an errant throw took Matt Carpenter off the bag. Two outs with an intentional walk mixed in later, the Brewers took a 3-run lead on a homer. Earlier in the game, Wong got caught in a rundown between third and home, ending the inning. Just how bad was this game for Kolten Wong? Let’s take a closer look.

There were 86 plays last night. Let’s focus on the ones Kolten Wong was involved in and how they impacted the game.

Second Inning

Michael Wacha induced a ground ball up the middle from Jesus Aguilar. Aledmys Diaz made a neat flip to Wong, who threw to first for the double play. How much of that play was due to Wong’s defense. Most of the credit should go to Wacha and Diaz, but let’s give Wong 10% responsibility on the play. The Cardinals win probability moved from 49.7% to 55% on the play.

Wong WPA effect: +0.53%

In the bottom of the inning, Wong grounded into a double play. This moved the Cardinals win probability from 58.8% to 51.1%.

Wong WPA effect: -7.7%

Fourth inning

A routine grounder to second increased the Cardinals win probability from 21.5% to 22.2%. Let’s give Wong 15% credit for the play.

Wong WPA effect: +0.1%

Wong was hit by a pitch in the bottom half of the inning, increasing the Cardinals win probability from 17.8% to 20%.

Wong WPA effect: +2.2%

Sixth Inning

Wong grounded into a fielder’s choice, decreasing the Cardinals chances of winning from 25.4% to 21.1%.

Wong WPA effect: -4.3%

With Matt Adams up on a 3-2 count, Adams hit a single to right field. Wong was running with the pitch and as he headed toward third, Chris Maloney’s arms were flailing wildly instructing him to go home.

First a screenshot.

Now in gif form:

Where to assign blame in this case is debatable, and it is also worth noting that by going all the way to third base in the eventual rundown, Matt Adams foreclosed whatever remote possibility Wong had of avoiding the out. In any event, for the purposes of this exercise, I will put the blame entirely on Wong. We can’t quite go to FanGraphs win expectancy graph for this one as the out occurred after a likely 1st and 3rd with two outs situation. That situation would have put the Cardinals at roughly 25% win expectancy and they moved down to 17.7% after the out.

Wong WPA effect: -7.3%

Seventh Inning

After an Orlando Arcia walk, the Cardinals turned abother double play. This one was a bit more routine, not requiring a fancy play from Diaz though a stronger throw from Wong was required so let’s give him 20% of credit on the play. The Cardinals win expectancy moved from 17.6% to 21%.

Wong WPA effect: +0.34%

Eighth Inning

Wong fielded a routine grounder that moved the Cardinals win expectancy from 14.5% to 15.7%. Let’s give Wong 15% of the credit here.

Wong WPA effect: +0.2%

With the Cardinals down 4-3 and runners on first and third, Kolten Wong singled in a run and put runners on first and second with one out. This increased the Cardinals win probability from 48.6% to 66.9%.

Wong WPA effect: +18.3%

Ninth Inning

Wong caught a fly ball. Very routine. Cardinals win probability went from 50% to 55.8%, but let’s only give Wong 5% of the credit.

Wong WPA effect: +0.3%

Tenth Inning

Here’s the play where Wong made the error.

The hit probability based on exit velocity and launch angle was 79%, but obviously Wong was positioned well to make the play. Carpenter could have come off the bag and tried to make the tag or done a better stretch with more optimal footwork, but let’s go ahead and give Wong all of the blame on this one as the Cardinals win probability went from 50% to 41.8%.

Wong WPA effect: -8.2%

Wong would not factor into any other plays. His gaffe in the tenth obviously came at avery important time and might have prevented Shaw from coming to the plate. Of course, if Wong hadn’t gotten a hit at the highest-leverage point of the game, the Cardinals might not get to the tenth at all.

Total Wong WPA effect: -5.5%

Wong didn’t have a great night and putting the full onus on him for both the baserunning blunder and the fielding error meant that Wong was a net negative for the Cardinals. In terms of win probability—factoring in the situation and score—the following players had worse nights than Kolten Wong when looking only at what they did a the plate: Greg Garcia, Randal Grichuk, Aledmys Diaz, Dexter Fowler.

It’s a team game. Kolten Wong had a rough night and he contributed to the loss, but he didn’t lose the game. The Cardinals did.