I don’t need to sell this all that hard. You come to FanGraphs. You’ve seen the articles about Eric Hosmer, his wildly fluctuating value, and how that stacks up next to his big free agency ask. The horse is dead already — rest in peace, horse. And yet, here it is. Another caution label to throw on Eric Hosmer, who is beginning to look more caution label than man now.

Statcast has been wonderful in both expanding the breadth and the depth of baseball analysis among both professionals (unlike myself) and hobbyists (hey, like myself!). Where PITCHf/x allowed us deep inside the world of pitching, many aspects of hitting were largely a black box until recently. With the aid of launch angles, exit velocity, and xBA we can judge not only the hitter’s results, but the process by which he arrived at them — is the hitter making quality contact? For Hosmer, his 25 home runs in 2017 might lead you to believe that he is. Statcast, as we’ll see, respectfully disagrees.

When it comes to types of contact, barrels are the crème de la crème. MLB’s glossary has the in-depth details, but in short — hit ball good, ball do good things. Statcast captures every batted ball event and allows us to take a closer look at who’s clobbering the ball on a regular basis. The leaders in barrel rate (Barrels per batted ball event, min. 200 batted balls) — Aaron Judge (25.74%), Joey Gallo (22.13%), and J.D. Kong (19.48%). Nothing out of place here. The laggards will surprise you just as much as the leaders did (in that they will not surprise you at all) — Dee Gordon (0.18%), Darwin Barney (0.36%), and Ben Revere (0.37%).  Hosmer’s 6.99% barrel rate ranks 121st out of 282 players, just above the average of 6.83%.

This not-terrible barrel rate is being masked by a well-above-average home run rate. Hosmer’s 22.5% HR/FB% ranks 30th in that same sample of 282 players. How do barrel rate and HR/FB% correlate?

Very well, actually. It seems my “hit ball good” theory has legs. Highlighted in red is Hosmer, and from a glance, it’s clear he’s pretty outlier-y. Using the equation from the best fit line and plugging in Hosmer’s barrel rate yields a pedestrian 14.34% xHR/FB%. The difference between his HR/FB% and xHR/FB% ranks 3rd out of 282. Yikes.

You might be wondering if HR/FB%-xHR/FB% even means anything. What good is knowing the difference if we don’t know the standard deviation or the distribution of the sample? Let the following bell curve assuage your concerns. Highlighted in red, again, is Hosmer.

I don’t have a very good conclusion for this. I’ve seen people mention his worm-killing tendencies. I’ve seen concerns about his defense. I’ve seen mentions of his BABIP-inflated career year. What I hadn’t seen yet was just how out of line his power numbers looked to be with his contact quality, and for a player seeking as much money as he is, that’s one more thing to be concerned about.

Playing with the wonderful new splits leaderboard that was just rolled out on these very pages has led me down a Tommy Pham-shaped rabbit hole.

Tommy Pham has a stat line that is currently boggling my mind.

.214 ISO, 10.9% BB%, .342 BABIP, and 9 HR in 183 PA…good to excellent offensive numbers, in my opinion. Yet despite all of these good to excellent offensive numbers, he sported a major-league-high 38.8% strikeout rate (min 100 PA) that dragged his wRC+ to a barely-above-average 105. This deserves some digging into.

Looking at this 15-game rolling K%, there were times this past season that his rolling K-rate was down to 20.8% (on August 12). The AMAZING thing happens the further right you look on that graph — he begins striking out at a rate that makes Bartolo Colon look patient, hitting a high of 66.7% in the middle of September. From the beginning of the season to August 12, Pham had a wRC+ of 126 — higher than the full-season numbers of Carlos Beltran, Nolan Arenado, and Jose Bautista. After August 12, his wRC+ was 40. 40! FOUR ZERO. That’s behind nine pitchers (min. 40 PA).

AND SOMEHOW

SOMEHOW

He managed to have a higher BABIP when he was walking through life in a strikeout-induced haze. After August 12, he ran a BABIP of .417 with a K% of 59.1%, meaning he didn’t put the ball in play much, but when he did, it was finding the holes. BABIP and wRC+ have an R^2 correlation of 0.23, so you’d sort of expect them to move up and down together. However, before he started striking out like he was afraid someone was going to outlaw strikeouts so he was getting them all in while he could, his BABIP was 89 points lower — .328.

That’s not just lower. That’s much lower. That’s the difference between Dexter Fowler and Albert Pujols. And somehow an 89-point difference in BABIP resulted in an 86-point difference in wRC+ in the wrong direction.

You’d think running a much higher BABIP would be the result of hitting more line drives. After all — that is the variety of batted ball that lands for a hit more often than any type.

BUT. IT. GETS. WEIRDER. He hit line drives 28.0% of the time up to and including August 12. After August 12, he hit line drives ONLY 7.7% OF THE TIME. So with a 28.0% line drive rate, he ran a .328 BABIP, but his 7.7% line-drive rate resulted in a .417 BABIP. WHAT KIND OF MAGIC IS THIS?

Well, you know. The magic of small samples. 183 plate appearances falls nearly 70 short of being half of a qualified season’s plate appearances. Weird things are going to happen when you are looking at smaller samples. Weird things are always happening in baseball; that’s part of its charm. We just don’t always notice because over the course of a season, some weird things will balance out other weird things and we’ll forget how weird things were at some point. That’s why it’s worth it to dive into the numbers — to remind yourself that fun things are always happening in baseball. You may even find yourself surprised with how interesting you find Tommy Pham at the end of it all.

With 2014’s baseball season winding down, end of year award discussion is starting to kick into high gear. It seems every day there’s a new article discussing X player’s case for winning Y award, when likely Z will win it.

Mike Petriello wrote an article discussing the NL Rookie of the Year race, and in it stated that it comes down to two players — Billy Hamilton of the Reds or Jacob DeGrom of the Mets. Ken Giles of the Phillies may not be considered a contender for the award, but by every statistical measure Giles’s 2014 rookie season compares  favorably with Craig Kimbrel’s 2011 RoY winning season.

In 2011, the NL Rookie of the Year award was a unanimous decision — Craig Kimbrel! Ice in his veins! 46 saves! Those strike outs! That slider! Could you vote for anyone else in good conscience?

Kimbrel was (and still is) a fantastic pitcher. But if his case for Rookie of the Year was unanimous, does that mean Ken Giles should also garner some consideration? And if Ken Giles had started the season at the Major League level and produced like he has so far, what would that look like? Would he have a better shot then? Let’s dive into the numbers.

Note: I am not an expert with projections. Therefore — all rate stats will stay the same between Ken Giles’s 2014 season and the full-season extrapolation. Sorry to disappoint.

First, some dashboard stats:

Both pitchers allow very low AVG despite having average to below-average luck with BABIP. Their LOB% is well above average, and they don’t allow a lot of home runs. As a result, their accumulated WAR values are both very good. Let’s dig into some rate stats to see how they compare there.

By FIP and xFIP, these pitchers are comparable. By ERA Giles has the advantage, which likely can be explained by the difference in BABIP.

Both pitchers have K rates that are simply awesome. Kimbrel gives up a few more free passes,  but makes up for it with some more K’s. As a result, their xFIP is nearly identical.

Now let’s look at how they achieve these results:

Stuff wise, they mirror one another. Both fastball/slider guys, with some real heat on their fastballs and sliders that fare rather well.
The real eye-opener — they even attack hitters the same way. Take a look at Kimbrel’s Pitch% heat chart in comparison with Giles’s. They are remarkably close to one another.

So we have two pitchers that have great stuff and get great results, but Giles is not considered a candidate. Why? Oh right:

Kimbrel was the closer and Giles was stuck behind the 13 million dollar man.

That should not sway our opinion and lead us to devalue the year Giles has had. We are smarter than that! If Giles had been up since April (and ready to face major-league hitters), in all likelihood we’d be talking about him when it came to NL RoY voting.

One last note: Minimum 40 IP, only two rookies have ever had a lower FIP than Ken Giles. Those occurred in 1884 (Henry Porter, 1.27) and 1908 (Roy Witherup, 1.31). Baseball history is long and filled with many numbers. Ken Giles ranks near the top of that list, and the two players in front of him played in the dead-ball era. What Giles is doing is special, and should be recognized.