Cavs demolished by Warriors, plus Tribe Off-Season
January 17, 2017NFL Draft: Malik Hooker, Marshon Lattimore ranked No. 2 and 3
January 18, 2017Baseball is a beautiful game, one where the sample sizes are big enough to utilize statistics to a greater degree of confidence than most other sports. The one area of the game that has been lacking is the defensive side where the metrics are both smaller in sample and less understood in terms of data collection. That is, until recently.
Defensive Runs Saved (DRS) and Ultimate Zone Rating (UZR) are defensive measures that have attempted to create statistics that are more comparable across players. Statcast takes things even further as there are many more things measured.
The latest release of defensive charts from Baseball Savant, however, demonstrates the initial dip into this fantastic world, and creates better ways to compare players. The issue is that there are graphical data charts without an easy way of using them to start discussing multiple players without using the dreaded eye test on the images. Here is an attempt to help navigate towards more merit-based debate with these charts.1
Explaining outfield defensive charts
Baseball Savant now has the defensive charts for outfielders. There are maps that show the full route areas that each outfielder covers, but that is the second-level of the data. It is important to first understand the basics, which are contained in the plotted charts at the bottom of these pages.
Defensive plays are charted in four different categories based on hang time of the ball against the distance traveled: Easy, routine, tough, and highlight. There are then separate charts for hits given up as well as outs obtained.
You don’t want to give up hits when the play should have been easy and you should get extra credit for when a ball should have been a hit but is turned into an out. Statcast allows us to figure out which of these batted balls are which (focusing on hang time and distance). In basic terms, fly balls, line drives, and bloopers are separated out to demonstrate how difficult they are for outfielders to make the play.
The above chart shows how difficult it is to obtain a hit when Kevin Kiermaier is ranging in center field (often referred to as the best center fielder in MLB). On the hits allowed chart, it can be gathered that he only allowed just one base hit within the easy and routine sections. Even the tough section of the graph shows only a few dots.
Conversely, there are many dots in both the tough and highlight sections of his outs obtained chart. The easy and routine sections are also littered with dots, which demonstrates that it was not a small sample size to explain why so few in those regions dropped in for hits. From this chart, it would appear the sterling defensive reputation of Kevin Kiermaier is warranted.
Probable Catch Ratio / Probable Catch Units
There needs to be an easy way to both understand what you are seeing and also to compare players. Enter the Probable Catch Ratio (PCR) and Probable Catch Units (PCU). Please note that there is no way in these numbers to account for arm strength and accuracy of throws, so there will be some variance from the DRS and UZR/150 metrics. These statistics are merely meant to complement them as they isolate the ability of the outfielder to catch batted balls.
The PCR is a way to compare defense of two outfielders ability to catch the baseball (normal constraints of sample size come into play). The ratio is used to both give credit to an outfielder who makes difficult catches more often as well as those who do not misplay easier batted balls. Instead of worrying about route efficiencies, top speeds, reaction times, and other metrics, the focus can simply be on the outcome. How many of those catches were made?
The simple equation becomes:
(outs recorded in highlight category) + (outs recorded in the tough category) :
(hits given up in easy category) + (hits given up in the routine category)
One of the advantages of using the PCR is that the type of defender is known as the propensity of an outfielder to make both difficult and easy plays is immediately visible.
The PCU is a single number to be more easily utilized as a comparison across players by dividing the left side of PCR with the right. The higher the number, the better the outfielder is at catching the ball. There are some caveats to be aware of before use though. The ability of an outfielder to make additional outs with their arm (throwing out runners) is not included. There should not be an assumption that the differences in PCU are linear in nature. Splits across the three different outfield positions is not yet publicly available. Still, it makes a handy additional tool to use along with DRS and UZR/150.
For example, Kiermaier’s chart above shows that he gave up exactly one hit in the easy and routine categories combined, while recording 43 outs in the highlight and difficult categories. Kiermaier’s PCR would be 43:1. Kiermaier would also have 43.0 PCU (43 divided by one) of defensive value. Lorenzo Cain’s chart shows seven hits allowed in the easy and routine areas with 29 outs obtained in the tough and highlight areas giving Cain a 29:7 PCR and a 4.14 PCU. While Cain is still a solid defender (as can be further seen below against Indians OF counterparts), he is no Kiermaier in the field.
Cleveland Indian returning outfielders
One of the first items you might notice above is how Abraham Almonte is not considered a good defender by the PCR metric in contrast with his DRS and UZR/150 scores. A deeper look into DRS demonstrates that four of his six units of value there are directly from his arm/throws. Therefore, it is unsurprising that a stat focused purely on being able to catch the ball is much less forgiving. Guyer’s negative arm/throw component, on the other hand, does not carry over to this score. It can be seen he is better at catching the ball than Almonte, but not as capable once the ball is in his hand. Combining these statistics help tell the full story.
It is not shocking that Naquin’s score is the worst of the bunch. Any fan of the Tribe is well-versed in his interesting routes to fly balls in the field. Chisenhall’s amazing 2015 season is not yet released for public viewing, so his 2016 will have to do for now. He was the Indians best fielder in terms of making the tough or highlight catch from this group, but his propensity to allow some of the easier plays fall in for hits precluded him from remaining in the elite group of outfield catchers.
Once again, an obvious defensive hole in center field develops from the above numbers.
Last Word
Baseball is entering an exciting age where everything from reaction time to velocity to route efficiencies can be tracked. Or, in the case of these new defensive charts, the flight time and distance of a fly ball. It will still be important though to ensure that this data is useful and explainable, which is why having some tools such as the PCR and PCU make sense. There will not and should not be one statistic that ends all discussion. It is more fun to discuss how to fit everything together to describe what is happening on the baseball field in ways that could not be fathomed a mere generation ago.
- And, if I fail spectacularly, then I at least outlined the issue itself. Right? [↩]
44 Comments
Am I allowed to be equally excited about the Encarnacion signing and terrified about the outfield both offensively and defensively? I can’t think of any other team in the league that would bat their entire outfield in the 6-9 spots while having the entire unit be *hopefully* average defensively.
RF should be average offensively and above average defensively. The rest of the OF is a scary, scary nightmare of potential.
Potential is like a fork in the road where left is good and right is bad. But, we don’t know who is driving the bus.
Do they statcast MiLB?
Many teams have their own internal items such as the Rays with Kinetrax that has been in The Trop for years. Some of the MiLB teams are rumored to have similar.
For public consumption, there is scant MiLB information – and not from Statcast. Even the MLB data from Statcast is not fully released. Still grateful for what they do show on baseballsavant.com though.
This is so exciting it dried out my mouth. Time for a refreshing drink!
http://media.giphy.com/media/JmJ9906MV9xvO/giphy.gif
Glad to be of service.
I did think about this stat creation with people who don’t like the advanced stuff in mind. That’s why my focus was on keeping it simple:
Instead of worrying about route efficiencies, top speeds, reaction
times, and other metrics, the focus can simply be on the outcome. How
many of those catches were made?
Mmmm, Nerdorade.
Personally speaking, I came to this article interested in the conclusions but not so much in the nuts and bolts. Kind of like when I talk to my motor head dad and brother about cars. FWIW, this piece suited my mind-set perfectly.
I am going to regret asking this but… How are errors rated in the model?
This is really good stuff Bode.
I’ve been finding myself looking at things like BABIP, FIP, EV and LA more and more often. It’s one of the reasons I come here and the guys at LGT do a really nice job on this too, although you kinda have to follow along there. I’ve been playing, watching and coaching baseball for decades, and I feel like I’ve learned as much in the last 18 months as I have the previous 20 years. I do find the divide between old school and statnerds interesting. It’s kinda foolish to ignore either.
MLB deserves credit for the investment they have made in technology without allowing it to ruin the game on the field. It most definitely influences and shapes games with lineups, matchups and the like, but it’s still the same basic game as 50-60-70 years ago.
I can ask Baseball Savant but I do believe they are factored into the “hit” chart. So, an error catching on a highlight play would be a dot there. One in easy, would be a dot there.
But, rarely are errors recorded for OFers on a catch. It has to hit their glove in most cases to be so. Most OF errors are on the throws, which is not part of this stat.
Thanks.
divide between old school and statnerds interesting. It’s kinda foolish to ignore either.
Completely agree. There is so much out there to learn but it doesn’t matter unless you have the “old school” guys who help you figure out how to apply it on the field. I have a few ex-MiLB & college players who help me take this kind of stuff and develop drills for my players.
Soooo, technically, this wasn’t an error…
https://uproxx.files.wordpress.com/2016/07/canseco.gif?w=650
Waiting for Next Year is turning into Wallowing in Fatiguing Nerd Yammer.
You can’t measure dirt on a uniform, dammit.
/hocks pint of tobacco juice onto dugout floor
weigh uniforms before & after game – then, you get a measure of both dirt & sweat & blood — all of those matter after all
#Nerdified
was an error recorded on that play? I never understood OF error recording. If you lose the ball in the sun and it falls behind you, sorry it sucks, but that is an error to me.
Apparently, it was ruled a HR.
http://www.cbssports.com/mlb/news/that-time-jose-canseco-allowed-a-home-run-off-his-head-was-23-years-ago/
The old school term for that is CFO, where C stands for cluster and O for Outfielder.
Makes sense from how they score things (though not how I would).
Ah, of course, the DSB Index. I knew you’d have the answer.
Albert Belle had some pretty excruciating moments in the outfield.
Is the white considered just uncatchable?
Yes, which shows just how good Kiermaier is at getting to the ball.
Jason Heyward is another fun example. He doesn’t have any catches in the white (not as fast as KK), but he did not let ANY balls drop that were easy or routine in 2016. Infinite PCU.
https://baseballsavant.mlb.com/player?player_id=518792&pos=RF&player_type=batter&season=2016&tab=defense_tab#
I like the sound of “four base error”.
Joey too….
What it must feel like to get $5M! This is pretty cool to see.
https://twitter.com/LindsayFox5/status/821745162967781377
Browns talk time!
I love silly season. Apparently, the HBT does, also…
http://thebiglead.com/2017/01/18/cleveland-is-trying-to-drive-down-the-price-for-jimmy-garoppolo-by-feigning-interest-in-tyrod-taylor/
You go nerds!
Foolish? Hmm. Not so sure. If statnerd enjoys baseball through analytics and old school enjoys baseball the old school way, that’s totally okay with me. Just enjoy baseball. If you like a combination of both, cool. I don’t think there’s a wise or foolish way to enjoy baseball.
Last year, didnt our ugly OF end up top 5-7 in most stats outside of HR, offensively? At worst, they’d be average this year, which doesn’t get me worried.
Jason McIntyre is the definitive clueless sports blogger in terms of just throwing out hot takes for clicks. He is completely irrelevent for any rational sports discussion. They destroyed that site when USA Today media group moved to Facebook commenting.
Absolutely, especially when you realize how little guys get paid while in the minor leagues. Not to mention the constant travel and relocation, all to chase a pay day that most likely will never come. Can’t imagine the strain that causes on wives and families.
Welcome, Superfriend. I am called Ham, because I enjoy ham radio. This is Email, Cosine, Report Card, Database, and Lisa. Your nickname will be Cosmos.
Who are the Rajai, Crisp, and Byrd equivalents on the 2017 roster. Maybe we still obtain them but it took constant handywork and some luck for the team to pull off last year’s OF.
Ok, maybe I’m a little late to the party, but did anybody else notice this Monday…
http://www.bostonherald.com/sites/default/files/styles/gallery/public/media/ap/2016/10/14/e399f021738f478aae2b1e4fffd9ed56.jpg?itok=XGhyhVdW
The season-long employment of Almonte and Guyer will more than offset some of the losses. Naquin having a sophomore slump is a legit concern.
Naquin dealing with his late season allergy to fastballs will be a substantial item on this matter.
Holy unsupported headlines, Batman! That headline baited me to click, but there was no steak for all that sizzle. Call me odd, but sometimes I like a little bit of “fact” to go with my “allegations.”
For what it’s worth, I hope the substance of the article is true (i.e., that the Browns want Tyrod Taylor). I’d rather have him than Jimmy G, and it would hold the “draft franchise QB” urge in abeyance for at least another year.
I like that Taylor would only cost $$ instead of picks + $$ that Jimmy-G would cost. I’m not sure whose ceiling is higher/lower though.
Given the options of:
Pick No. 33 + $15m/year for Jimmy-G
vs
Pick No. 33 + $15m/year for T.Taylor & P.Mahomes
I’m a bit conflicted as to which one would be better (Kessler remains in both cases)
I guess I’m of the mind that (assuming the QB ratings are correct – and I know they’re misleading), I’d rather have (a) sturdy #10 rated QB (Taylor) + Kessler over (b) basically unknown, if extremely hopeful, quantity (Jimmy G) plus Kessler. If we can add Mahomes, as you suggest, to (a), then it’s a no-brainer for me. Though, if we can get Taylor, I don’t even want Mahomes. I would be comfortable – like flannel-lined jeans and a Carhartt jacket on a cold day – building the team, at least for the short-term, around Taylor/Kessler.
At first I thought you were referring to Bode’s headline above as clickbait. I know when I read “Introducing Probable Catch Ratio and Units,” I was hooked.
I am putting that recommendation on the back cover of the book I’ll never write.
Considering the Bills are cutting bait with Taylor despite needing a QB, I’d feel more comfortable with a project like Mahomes in my back pocket. If only one of he or Kessler pans out long-term, well we only need one at a time.
I mean, at this point, Bode’s headlines just elicit a Pavlovian response from me. I see them, I click. Then, when I realize he’s talking analytics, I just drool. But not because I’m looking forward to anything.
http://i.giphy.com/N8ifh4i3zOAMg.gif
Facts? Dude! It’s silly season.
Embrace the ridiculousness.