LAKELAND and PORT CHARLOTTE, Fla. — We know the immense value teams have derived from applying PITCHf/x, Statcast and other new-age data tools to decision-making. We know this information has helped enlighten the public, including journalists and bloggers, to better understand performance. But I suspect we’re just really scratching the surface with how the big-data age is going to help players.

We know a number of pitchers have used the data to make real changes to pitch type, release point and location. Hitters have tools to better understand their quality of contact. There could be enormous benefits to injury prevention and on-field efficiency from the data being collected. But there is a practical daily use all players could and perhaps should glean from the avalanche of information that has poured into the game right now: the keeping of sanity and reduction of the duration of slumps.

Baseball is often characterized as a game of failure. This is particularly true for hitters, of course: even the best of hitters are unlikely to reach base in a given plate appearance. All players must battle through slumps, through challenging periods. And for all the game’s history leading up to the PITCHf/x and Statcast eras, players were often making adjustments with only anecdotal, observational feedback.

Think about the player who, in the midst of a slump, alters his batting stance; the pitcher who searches for a new arm slot or grip. Even with these minor adjustments, players might be making needless changes that are detrimental and could deepen a slump. For much of the game’s history, performance and skill was only quantified through box scores. We know now, though, how much of that performance is dependent on teammates and opponents, fortune often tied to the BABIP Gods.

One criterion for assessing the value of the data and technology available today is whether it helps players make rational adjustments — and whether an adjustment that has been made is working. J.D. Martinez has been in the news lately as an outspoken early adopter of the fly-ball philosophy.

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Back in 2010, the Rays used their 31st round draft pick on a right fielder from Parkland College, a JC that hadn’t produced a Major Leaguer since Juan Acevedo, who was drafted in 1992. This particular pick was the 941st selection in that draft, and no player taken 941st overall had ever made the majors. The Rays offered just a $75,000 signing bonus, as expectations for the long-term value received by a 31st-round pick are generally not very high.

That bit of context is important to keep in mind when reading that Kevin Kiermaier, that long-shot prospect Tampa selected seven years ago, just signed away the likely remainder of his productive years for $53.5 million in guaranteed money. At a time when many of the best young players in baseball have eschewed the early-career extensions that the previous of generation of stars signed up for, Kiermaier’s context helps explain why he’d sign a deal that will, more likely than not, cost him money down the road.

By signing a six year contract that likely includes an option for a seventh year — the Rays generally don’t sign long-term extensions that don’t include team options — Kiermaier is agreeing to sell his first three free agent years in exchange for a significant guaranteed income stream right now. And given that he didn’t get a big signing bonus and has made close to the league minimum in his first few years in the majors, this is legitimately life-changing money for him. Even after taxes and agent fees, he’s now going to bank at least $30 million during his big league career, allowing him to retire comfortably whenever he’s done playing.

For a guy who wasn’t heavily recruited out of high school, wasn’t even considered the best prospect on his JC team — Baseball America put RHP Danny Winkler ahead of him on the Illinios state draft preview — and was never considered any kind of top prospect, it’s probably not easy to turn down this kind of money. But while Kiermaier is probably happy to know he can play most of his career with the same team and retire a rich man, this is the kind of contract that should incentivize the MLBPA to fight for a total overhaul of the arbitration system.

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The Dominican Republic hadn’t lost a game in the World Baseball Classic since 2009. They’ve been a juggernaut, an unstoppable force barreling through immovable objects. That ended last night when Puerto Rico beat them 3-1 in a game that was much wilder than its score would indicate. One of the more dazzling plays was Javier Baez putting a no-look tag on Nelson Cruz on an ill-advised steal attempt.

When we say ill-advised, we really mean it. For one, Yadier Molina was behind the plate, and Yadi has been of the best in the business at throwing out baserunners. Cruz can only really be called a baserunner because of the fact that he does, in fact, technically run between the bases, even if “lumbering” may be a better verb for this scenario. Cruz is a large, 36-year-old adult human being. He hasn’t recorded a positive baserunning figure since 2010. Whatever speed he once possessed (24 steals in Triple-A in 2008!) is almost entirely gone.

There’s also the factor of Baez, who has revealed to the surprise of many that tagging is a real skill. So, yeah, we’re not sure why Cruz was running here, especially with two outs and an 0-0 count on Adrian Beltre. But run he did, and well, this happened.

Baez didn’t even look at Cruz. He was pointing to Molina and grinning like a kid on Christmas before he even caught the ball. You silly, silly man, he’s probably thinking to himself. Thanks for the free out. Cruz is out by a mile, and Peurto Rico gallops off to the dugout. Goddamn, Javy Baez. Goddamn, Yadi. Jeez, Nelson Cruz.

But hold on a second, here. Slow-motion video affords us the chance to take a closer look at plays like this. It also affords us the chance to make complete and utter fools of ourselves, as I may be about to do here. But I’ve been writing here long enough for all of you to get used to that by now, so hang with me here for a second. Let’s roll the film again.

Molina’s throw beats Cruz to Baez. The ball is in Javy’s glove right as Cruz is starting to slide. Nine times out of ten that’s game over, man. But was it? It initially looked like Baez got the tag down on Cruz’s knee, and Cruz was dead on arrival at second base.

This isn’t an episode of CSI, so I can’t tell the lab tech to enhance the video and clean up the pixels. I can, however, tell you that the umpire was on the shortstop side of second base, and that his view of Baez’s glove was obstructed by Cruz’s legs and tookus. And here’s a warning, because this is about to turn into a bad knock-off episode of CSI.

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Earlier today, my first post about catch probability was published. In that post, I mostly looked at the two years of information, together. In here, I’d like to keep the two years separate. I mean, this is a whole new data source, with a number of potential applications. Why would I ever write just the one article and stop there? I have a weekly quota to hit, and this is better than whatever else there is to analyze.

Catch probability is a new Statcast metric, which you can read about here. As complicated as it might seem, it’s actually quite simple to understand, and it can give us better answers to questions people have been asking for decades. This is where you can find all the data, so you can poke around on your own. This is all brand new, and it’s kind of a first draft. The data will improve as adjustments are made for batted-ball direction and for outfield dimensions. Already, though, we can learn from what’s been provided.

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Have you seen what Yonder Alonso is doing this spring? You might not recognize it. If he qualified, his .421/.560/.789 line would the third-best in baseball. While it’s easy to dismiss a spring fling from an established player, this player spent the offseason thinking differently. Now he’s moving differently at the plate, too.

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The Reds’ pitching staff was absolutely dreadful last year. Their rotation and bullpen were both the worst in baseball. With a ghastly -0.5 WAR, their staff was the worst since the 1800s, which basically means it was the worst of all time.

Not much has changed since last year. Here’s the current depth chart for the Cincinnati rotation:

Brandon Finnegan is at the top, which is fine, I guess. After that, however, things go downhill in a hurry — especially with Homer Bailey and Anthony DeSclafani slated to open the year on the DL. For example: both Bronson Arroyo and Scott Feldman are apparently not only still pitching, but are penciled in for 250 innings in Cincinnati’s rotation. The rest of the list is made up of unproven youngsters. Each of them has some promise, but none have had much success in the major leagues, either. Hence their middling projections.

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Here’s the thing about catch probability: It’s existed for close to two decades. It’s at the heart of what we refer to as the advanced defensive metrics. Defensive Runs Saved, Ultimate Zone Rating — they couldn’t exist and do anything without catch probabilities in some form. It’s just that, for the longest time, those probabilities were generalized, educated guesses. You might’ve heard that baseball has entered the information era.

Here’s a weekend tweet from Daren Willman:

Here’s the new @statcast catch probability leaderboard we introduced @sabr https://t.co/I1NDOCRVFO

— Daren Willman (@darenw) March 12, 2017

If you missed the link in there somehow, here it is again: the Statcast Catch Probability Leaderboard. We have most of two years of Statcast information, and now we’re getting to see it applied to player defense. Specifically, in this case, outfielder defense. If you don’t entirely understand what catch probability is, here’s the MLB.com glossary entry. Take a given fly ball or line drive to the outfield. What are the odds a given batted ball is caught? Statcast can tell us, by considering hang time and necessary distance to cover. This is the start of something beautiful.

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Last April 4, Adam Jones swung at the first pitch two times. He swung at the first pitch five times on April 6, and then he swung at three more first pitches on April 14. By bedtime April 20, he was up to 16 first-pitch swings. The next day, he added four more.

Teammate J.J. Hardy also swung at the first pitch 16 times. All season. Out of 438 first pitches.

Hardy has never been aggressive early on. His highest-ever first-pitch swing rate is 11.9%, set as a rookie. His career rate is 8%, against a league average north of 27%. Last year, though, he was particularly patient. Not that Hardy is aggressive in any count, but I’ve highlighted him in this plot of first-pitch swing rates and all-other-count swing rates.

The next-lowest first-pitch swing rate was more than twice as high. Hardy’s other-pitch swing rate isn’t so weird, around 47%. But he swung at the first pitch just 3.7% of the time. The other players in his peer group, by other-pitch swing rate, went after the first pitch 25.7% of the time. It’s not that Hardy would never go after the first pitch, but every single time, it came as a surprise.

You’d figure Hardy might be really selective then, right? Welp! Of the 16 first-pitch swings, seven came at pitches out of the zone. Seven swings put the ball in play, but Hardy wound up with one hit, on a grounder. Perhaps it’s additionally worth noting that Hardy took all of three first-pitch swings when there was no one on base. When he was aggressive, mostly, he was just trying to move runners around.

It should go without saying that I don’t know exactly what Hardy’s plan is, because I’m not J.J. Hardy. He might just feel a lot more comfortable after he sees one pitch out of the hand. But just looking at this from the outside, Hardy could probably stand to just pay closer attention from the on-deck circle, because he’s been taken advantage of. Unsurprisingly, Hardy last year had one of the league’s very highest first-pitch zone rates. And no other hitter in the game had a higher percentage of his plate appearances advance to an 0-and-1 count. Hardy went through that count in about 61% of his trips. The average was 49%. If anything, it might be strange these rates weren’t even higher.

Again, hey, Hardy’s his own man. He’s coming off a much better season than the one he had the year before, so more power to him for his 2.3 WAR. He’s not doing everything wrong. But that’s an Orioles lineup full of guys unafraid to take an early hack. Maybe Hardy’s just trying to be different on purpose, but it seems to me he’s doing himself a disservice by watching as much as he does. There has to be a better way to get yourself prepared.

Shifts. They’re everywhere! They take different forms, some more extreme or unusual than others, but this is, without question, the era of non-traditional defensive positioning. Defense will never again look like it used to, because there’s no reason to go back. I was watching a WBC game the other day and the broadcasters pointed out that one of the teams wasn’t shifting. That’s what’s newsworthy now. We take defensive movement for granted.

This is an InstaGraphs post, instead of a front-page post, because there’s nothing surprising about the images or data that follow. I just want to show you, graphically, how the sport has changed over the past decade or so. You know we have numbers like pull rate, correct? That information, on the league-wide scale, seems to be stable going back to about 2006. Here is how batted balls have been distributed:

Super consistent. Balls are being pulled as often as before, and they’re being sent the other way as often as before. Maybe you expected that, or maybe you didn’t! I’m not in your head. Let’s just move on to the more interesting stuff. Here is league-wide directional wRC+:

The pull line has stayed consistent. Yet there are recent increases in the other two lines. How about we focus on just batting average on balls in play?

Pull line down. Opposite line up! This is all very intuitive. To go one step further, here is the same plot as above, only in this one I’ve included only ground balls:

I could’ve broken out right-handed hitters and left-handed hitters, but these days there are adjustments against hitters on both sides. And anyway, all this does is prove what you presumably would’ve already guessed. Pulled ground balls were never great, but they used to be hits more than a fifth of the time. That rate has dipped, because almost everyone pulls the majority of their grounders, so that’s where the defenders are going in greater number. Grounders back up the middle have seen a slight rise in success, with a weird spike in 2014. And then the line for grounders to the opposite field has taken off. The BABIP as recently as 2009 was .287. Last year it was .373. You know what those grounders look like when the defenders have moved. They’re frequently routine rollers, hit to an area where nobody is.

The end result of all this? A decade ago, the league BABIP on grounders was .239. Last season, the league BABIP on grounders was .239. That isn’t meant to suggest that shifting in general is a complete waste of time. It’s just — it’s complicated. Baseball will find its own levels, regardless of what you want or expect.