Pitch F/x Results through Three Weeks

With the day off today it seemed like a great time to dig into the pitch f/x data on the season thus far. As always, data comes from BrooksBaseball with my own buckets and formulas scattered throughout. There’s a lot to cover so I’m going to nix the terrible jokes for once and dig right in starting with batters:

The top two tables show the number of pitches and total run values accrued so far by pitcher handedness and pitch type. The raw totals for total run values show some scary stuff with the Rays only accruing positive value on lefty breaking balls and righty fastballs. Lefty fastballs have absolutely killed this team with righty breaking balls having the next worst impact.

Moving down to the middle two tables we see the prior stuff adjusted to show each pitch as a percentage and run values per 100 pitches. The Rays are seeing more breaking balls from righties with lefties subbing in change ups instead. As an outline, these are great ways to attack righties. The breaking ball from righties has been thrown early and often against Myers, Rodriguez, and Jennings, while Zobrist is seeing a number of fastballs where pitchers have had to be more cautious with the heater in the past. Joyce is seeing a ton of change ups from righties while Longo is getting almost strictly fastball/breaking ball.

Using RV/100 we see that Joyce has been a monster with Longoria, Jennings, and Zobrist being quite valuable, overall. Loney and Hanigan have been similarly above average, and Sean Rodriguez has put up numbers due to selective plate appearances. The other end of the spectrum shows a split dichotomy between guys that can’t hit and guys that aren’t hitting. We see Guyer, Molina, and Kiermaier in the former while DeJesus, Forsythe, Myers, and Escobar make up the latter group. While I wouldn’t expect much offense from the first group we should expect the second to hit better than they have which should raise the overall level of the offense. The total line shows us just how far below average the offense has been thus far.

Lastly, I wanted to take a look at the percent these pitches are turned into swings and in the zone. As with the stuff above, there’s too much to walk through, but it all does a great job of showing what these guys have done so think of it as a reference tool as much as anything. I’ve been saying that I think Forsythe is too passive, but the swing numbers indicate he’s actually swinging too much especially in contrast to his zone percentages. Let’s look at this stuff from the perspective of our pitchers:

Zooming right ahead to the middle table I wanted to focus on the relief pitcher shuttle bus that we’ve seen so far. Boxberger shows a three-pitch mix to righties, but shelves the breaking ball against lefties. Riefenhauser hasn’t thrown a change yet throwing a ton of breaking balls to both types of batters. Beliveau is a different sort of lefty using his fastball a ton. Moving over to the RV/100 table we see that Boxy has been death to lefties and righties, alike. Beliveau has seen similar success (in 18 pitches!) and Riefenhauser had a lefty hit his fastball. The samples are really small here so this is mean to be more of an introduction on these guys.

These three guys have been good out of the pen, but they aren’t alone. Gomes has been slightly better than averge. Balfour has been very good despite some ball four issues, at times. Heath Bell hasn’t been very good, but he’s posting nice numbers against lefties. Jake McGee has been lights out using his curve a little here and there, though not seeing great results on the pitch it gives the batters something else to think about. Peralta has also been very good and Josh Lueke feels like a dead man walking.

Lots more here to talk about, but I hope this gives some insight in how these guys are faring roughly 10% into the year.

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Performance Issues

It’s no secret that the Rays “offensive attack” has focused more on the former and less on the latter thus far. So far they’re 26th in runs (47), 29th in batting average (.221), 20th in on-base percentage (.306), and 25th in slugging percentage (.353). Gross. Ineffective. Flaccid. These are just a few of the words that can describe the Rays team offense after two plus weeks.

You can make a litany of excuses. Maybe we’ve faced good pitching? Maybe we’ve played in parks that aren’t conducive for offense, including our own. Maybe guys are being asked to face pitchers where the match up is not ideal? Well we can use the latest iteration of the match up tool that adjusts for park factors. The idea here is to compare the player’s actual wOBA to what we would project using the match up tool and we can also use these figures to calculate wRAA and expected wRAA to see how all of this accrues:

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Rethinking Park Factors

Fangraphs does an excellent job of tracking park factors for each MLB Stadium, but I’ve always wondered why it seems to over-rate the Rays bats while under-valuing their pitching. Everyone knows intuitively that each park plays differently when it comes to scoring runs, but a bit more nuance shows that each park favors various outcomes differently, as well. Currently, wRC+ appears to use the “basic” PF for adjusting wOBA for park, but this may not be the best approach. Come along for the ride as I attempt to find a better way to adjust for park effects.

First things first, what are the basic inputs for wOBA? We know that scoring runs is dependent upon getting on base and hitting for power. While OBP and SLG do a good job of representing each of these aspects they have flaws due to having different denominators (which is why you should almost never use OPS), but also due to their own inputs. OBP considers a walk and a home run to be of equal value while SLG considers a home run to be worth four times as much as a single, while not even including walks. The beauty of wOBA is that it combines both of these things and uses linear weights to derive the actual run expectancy of each outcome. You can scale these things to league offense, but I prefer to use the static coefficients that you find in the link above:

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Series Preview: Rays at Orioles April 14 – 16

Now that the matchup tool has been park adjusted I wanted to take a stab at previewing the next Rays series that starts tonight at 7 PM at the Baltimore Orioles. Game one features Wei-Yin Chen taking on our own Chris Archer:

Longo should be the class of this game, but Crush Davis is right there with him and then we see a couple of more Rays slated for success. Nick Markakis might be a guy that’s easy to sleep on, but he matches up very well with the Chris Archer that has shown a significant platoon split in his short career. This also bodes well for Clevenger as he might see a start with Wieters already seeing so much time behind the dish. Archer’s splits will help him against two very dangerous hitters in Cruz and Jones, but this is a fairly balanced lineup.

Game two pits Jake (H)odorizzi against the righty Miguel Gonzalez.

The cream shows a pretty even split between our good hitters and theirs, but in the middle we see the O’s having a bit of an advantage. Hodor doesn’t have much of a baseline, still, and the projections don’t know about his Thing with only two starts factored in for this year, but Gonzalez has a longer track record with ok to good results.

The final game pairs the best from each team as our own David Price seeks to extend his success against Chris Tillman.

We should match up pretty well with the righty and Price should only have a couple of landmines to work around in Cruz and Wieters. The Rays need to continue to take two of three, especially intra-division, and they seem well-poised to do so here. The Rays have been abysmal against lefties to start the year, but getting off on the good foot tonight should set them up well to take this series. I don’t have time for a full write up, but here’s our offensive performance through April 11:

WordPress has decided to make it so that you can’t resize images so you’ll probably want to open that in a new tab. Yuck city versus lefties and we haven’t exactly gone out and achieved against righties, either.

Lastly, I wanted to show the bullpen matchups:

The top table shows the matchup projections for each of our guys versus each of theirs and the bottom adjusts for if our hitter is is coming up in a pinch. I think this could be handy for trying to isolate who should be facing whom in those high-leverage late innings. Here’s how the Rays match up:

I have not included Brad Boxberger who should be available for this series so make fun of me if you wish. Be careful with Chris Davis and don’t let the other one to two scary guys beat you on a given day and the Rays should bode well. It sure would be nice to see the offense get going, but at the very least we could use some deep starts from each of our guys.

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First Time Through the Rotation

No predictive value here, but I think it would be fun to take an early look at what our pitchers did the first time through the rotation. I’m using he Pitch F/x data from Brooks Baseball with some of my own calculations. Those that are familiar with the site will recognize the format here so I won’t spend a ton of time explaining. Let’s start by looking at what they threw and how effective it was to lefties, righties and both:

 

In the top left we have the number of each type of pitches thrown to both types of batters and the total. Fastballs include two-seamers, four-seamers, sinkers, cutter, and this time only I’m including splitters in with fastballs instead of the second type of pitch, change ups. The third type are breaking balls composed of curves, sliders, and knuckle curves. I do not include intentional balls nor pitchouts.

In the bottom left the raw number of pitches is expressed as a percentage. Note that the total columns show the platoon split faced. As an example, Alex Cobb faced 51% lefties while Moore only threw 9% of his pitches to lefties. You can see how each of our pitchers approached a batter. For instance, among starters, Alex Cobb threw the most breaking balls to lefties while Matt Moore didn’t throw a single one. In fact, Moore only threw fastballs to lefties. Cobb and Odorizzi were the only starters to throw change ups to lefties, with Odo throwing his new pitch almost a third of the time. Look through and find your own interesting things, but how about Cobb only throwing 42% of his pitches as fastballs. Odo was in a similar boat, but the other end of the spectrum shows Price, Archer and Moore throwing over 70% fastballs.

Moving to the top right we find the total number of runs either earned or given away for each pitch to each type of batter. Starting on the right with the totals we can see the relatively poor performance from Cobb and Moore. Cobb struggled mightily with lefties and uncharacteristically we can see that his very good change was a big reason why, though the breaking ball wasn’t doing him any favors. The curve was strong to righties, but they had success on the fastball. For Moore, his problem related to all those righties and the face that his curve was garbage and his fastball wasn’t a whole lot better. Odorizzi garnered the most runs saved based off the back of his change to lefties and fastball to righties.

In the bottom right we have the total runs adjusted per 100 pitches to attempt to put all these things on an even keel. It breaks down when only a handful of pitches have been thrown, but this is less of an issue over an entire season so we’ll spend more time with that later in the year. For now, let’s move over to a couple of other things I like to quantify:

 

You may want to refer to the earlier chart for the raw number of pitches thrown in each scenario, but for this chart we’ll focus on the pitches thrown in the called zone, on the left, and the pitches that were swung upon, on the right. It’s impressive that Archer and Odorizzi were able to throw their breaking balls in the zone to lefties more than 60% of the time and Cobb threw his change up in the zone almost 80 of the time. Overall, Odo threw nearly 60% of his pitches to lefties in the strike zone while he’s chased by Cobb (53%), Archer/Cobb (45%) and Moore (40%). Against righties we see a different story with Price leading the way at 63% strikes and followed by Archer (54%) then Odo (54%), Moore (48%) and weirdly Cobb at 42%.

Lastly we can flip over to the % of pitches that drew swings. Overall, we can see that Cobb only had 37% of his pitches get swung upon while Odo did him one better at only 36%. The other side sees Price leading the way with 49%, nearly half of his pitches, were swung at with Archer at 43% and Moore at 40%. There’s a lot to glean here so I’ll leave it to the reader to tell a tale or two, but I wanted to share this to give an indication of what we saw on the field. I hope to continue to bring this as much as I can as it should make a nice comparison start to start.

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Chris Archer Wages War On Parallel Universe Chris Archer

Some believe in the idea that there are infinite parallel universes out there in the yonder. Carbon copies doing different things, living different lives, in similar worlds. We’re familiar with the concept via 1970′s science-fiction writing, but today I wanted to focus on just two of these universes. In Universe A we have calm, cool, mild-mannered Chris Archer. He is focused, he is unemotional, he carries the swagger of a killbot designed for one purpose, to kill batters without once taking pleasure in his mission.

In Universe B we have wildman Chris Archer. He starts bar fights and gets fired up when the Jets turn the ball over. This Chris Archer is the emotional one that is prone to snap before begging your forgiveness. He’s polite, but that doesn’t stop him from enjoying a cigar after taking your mama out for a spin. This Chris Archer is liable to do anything, as he once sang along, probably, “As long as I got my beretta, I’m down for whateva.”

These Chris Archers will never meet. They will never know each other exists. They will go on to have wildly divergent career paths due to mental maturity, physical luck, and those Gottdang dinosaurs that we thought were extinct, but in one of these universes they are brought back into existence by a totes mean necromancer named Jabari Parker (parallel universes, brah).

Yesterday, I mocked up what some different scenarios would look like for Chris Archer… Continue reading

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