Earlier this week I was playing some MLB “The Show” – because that’s something we baseball writers now not only do but also write about. Crazy world we live in. Anyway, maybe this has changed in the ’20 version (I am stuck with ’19) but in my game, Yadier Molina has a speed rating of 0.
No joke, I hit a ball into left-field and Molina was thrown out at first. Of course, I didn’t yet know what I was doing, and maybe/probably/definitely I was spamming buttons and causing all kinds of base-running hilarity. (Cue the circus clown music.)
My baseball gaming career has consisted of mastering Tony LaRussa Baseball II on my IBM PS2 at age 15, followed by 25-years of colleges/wife/kids/jobs and MLB franchise simulators, and now a pandemic-fueled, kitty-pool-deep dive into The Show ‘19. If you see me online, play me! You’re guaranteed to win.
It got me thinking, though: is Yadier Molina the slowest baseball player in the game? Not like videogame the slowest but actual real-life the slowest?
Of course, Baseball Savant has a stat for that.
Statcast measures everything that happens on a baseball field. From how fast a ball is hit to how much a curveball spins. They even measure the average length of footlongs at Busch.
Ok, they’re still working on that last one, but I could go for a stadium dog right about now.
They have a simple stat called “Sprint Speed” that measures, as one would guess, the sprint speed of players at various distances. The magic Statcast cameras track players from 5 feet – essentially a player’s “jump” – to 90 feet – the distance between home and first. They use weak contact like topped or weakly-hit balls to gather their measurements. The idea is to choose plays where the player has the incentive to sprint as fast as possible for as far as possible.
The results leave a less-than-desirable sample size. It only takes 10 such incidents for a season to qualify for MLB’s sprint speed leaderboard. Yes, 10. Obviously, that’s a sample size of questionable value. Take all of this with a healthy level of skepticism.
For the Cardinals, that qualifier was still too restrictive, so I cut it back to 5 qualifying incidents and ran the numbers from 2019. The actual sprint times by distance are pretty meaningless, so instead, I sorted the information by percentile ranking. This gives us a nice chart of reds, whites and blues that is both highly patriotic and informative.
My take away? The young Cardinals are fast. Like my pirated version of Tony LaRussa Baseball II on a PS2 when I used a boot disc fast. (That was a thing, kids. Check AltaVista.)
I was surprised when Tyler O’Neill came out in the top spot. O’Neill’s peak of 96th percentile at 90 feet just barely surpasses the left-handed version of Tommy Edman and Harrison Bader, who reached the 94th. Both Bader and O’Neill struggle out of the box. The lefty version of Edman, on the other hand, just flat flies all the time. He’s in the 71st percentile at 5 feet – compared to 42nd for O’Neill and just 13th for Bader. Edman reaches the 93rd percentile at fifteen feet and never falls below again.
Interestingly, Edman isn’t quite so fast batting from the right side. He’s much slower out of the box and doesn’t reach the same peak speed. Why? Remember the qualifiers I mentioned earlier: tiny sample sizes and limited opportunities.
The rest of the chart falls into four neat-and-tidy categories.
Speedsters (+92nd percentile): O’Neill, Edman (LH & RH), Bader, Thomas.
CF’ers & MI’ers (61-74th percentile): Wong, Munoz, Fowler (LH)
The Slow (34-44th percentile): Fowler (RH), Ravelo, Ozuna, Goldschmidt
The Catchers (0-25th percentile): Martinez, Knizner, Carpenter, Wieters, Molina.
Speed isn’t evenly distributed across the roster. There are 17- and 18- points separating the top three categories. The Cardinals’ speed is limited to its middle infielders and young outfielders, which is probably true for most teams.
Our lowest two tiers have just a 9-point spread between them. That’s where we find former Cardinal Jose Martinez and Matt Carpenter, who are both “catcher” slow.
Molina, as you can see, ranks in the 0th percentile across the board when measuring weak ground balls. I’ll let you draw your own conclusions about why that is.
He’s not the slowest player in the game, though. The following image has sprint speed distributed by position. If you start from the left, Yadi Molina is not the last blue dot. That unholy honor belongs to Briann McCann. The next slowest is a former Cardinal known for foot problems - Albert Pujols. Then falls Molina.
While all of that is interesting, it’s more fun to play the little game that MLB included in their sprint speed stats page. The web developers at MLB were bored one day and they created a script that allows fans to put any 4 players in the game into a virtual race. The app then runs the race over 90 feet to see who would win.
I ran two such contests. The first pit the top four finishers on the Cardinals against each other – O’Neill, Edman (LH), Bader, and Edman (RH). I used Edman (RH) over Lane Thomas because Edman (RH) was consistently faster than Thomas throughout the race until the 90 ft mark.
Here’s the resulting race, which I converted to video and rolled in succession for 20 seconds.
Played with Baseball Savant's Sprint Speed tool. Who would win in a race? They'll show you. Here are the top four finishers in Sprint Speed on the Cardinals in 2019, converted into a rolling video. pic.twitter.com/hVzQ0zgASP— Jason Hill (@JPHill_Cards) April 8, 2020
That tells us nothing that the data didn’t, but it’s still a fun toy. The difference between these players is minuscule at best.
The second race featured four players spread throughout the rankings: Bader, Wong, Ozuna, and Molina. This helps show the difference between one of the fastest players in the game compared to one of the slowest.
Played with Baseball Savant's Sprint Speed tool. Who would win in a race? They'll show you. Here is a sampling of players spread throughout the Cardinals' rankings in Sprint Speed, converted into a rolling video. pic.twitter.com/Ch7YWn61io— Jason Hill (@JPHill_Cards) April 8, 2020
Here is where you can see the difference between players. The difference between Bader and Wong isn’t all that great – a step or two at most from home to first. The difference between Wong and Molina, however, is pronounced. Molina is 15 feet behind Bader over 90 feet. That’s a loooong way.
If you want to play with the app more, you can do so here. Have fun!