After 20 losing seasons, the Pirates made the playoffs in 2013, 2014, and 2015. These were the fruits of their new strategy on pitching and defense: to generate lots of grounders and use infield shifts to convert many more balls in play into outs. Analytics are the foundation of Pittsburgh’s plan, and Travis Sawchik summed up an important component of their ground ball-creating effort in Big Data Baseball:

[Dan] Fox and [Mike] Fitzgerald looked into the coaching staff’s questions about pitching inside, and prior to the 2013 season they found that pitching inside would indeed have a psychological effect on batters that would create even more ground balls and further enhance the plan. The numbers showed opponents were more likely to pull outside pitches on the ground after being pitched inside earlier in the at-bat. After being pitched inside, players were less willing to aggressively lunge at outside pitches.

It’s a strategy born of logic: throw inside, heighten a batter’s fear of getting hit by a pitch, and half-hearted, lousy contact will come. Yet when I modeled groundball rates yesterday, the inside fastball variables emerged as useless predictors. Whether inside heat came on the previous pitch or earlier in the plate appearance, these factors’ percentage impact figures never rose above a measly 0.1 percent.

I also tested a more general version of this variable: the previous pitch’s horizontal location, a factor that applied to all pitch types. It did show that an inside pitch ahead of a pitch put in play does result in a bit more grounders. But its percentage importance in each model didn’t even hit 2.5 percent, and for all pitches, crowding a batter by an extra inch doesn’t even raise groundball percentage by one-fifth of a percent.

Why is there a discrepancy between my models and the Pirates’ analysis? It’s possible there’s more to the Pirates’ theory the models don’t assess. Sawchik writes that “opponents were more likely to pull outside pitches,” so perhaps the implication is that grounders become more tightly distributed on the pull side. With more predictable spray angles, shifting one’s infielders becomes easier, and more balls in play can be converted into outs. The Pirates also may have kept more nuanced insights under their pillbox hats. Perhaps through analysis of HITf/x data, Pittsburgh learned to create weakly-hit grounders.

Still, these psychological games shouldn’t be the focal point of a ground ball-producing plan. I make that assertion for another reason, beyond insignificant model results; it’s because the models correctly find the Pirates to be baseball’s most groundball-devoted team in the past three full seasons. Pitches thrown by the 2013–2015 Pirates had an average 64.3 percent predicted groundball percentage, highest of any team and 5.3 percent better than league average. It’s unlikely the models are missing a Pirates-specific strategy that would boost their groundball percentage to even greater heights.

We can see the Buccos’ devotion to grounders by another extension of the models — the extent to which pitchers’ groundball rates changed when they were newly acquired by Pittsburgh and plugged into the team’s philosophical “system,” affecting pitch selection and pitch action. How much did the Pirates reshape pitchers’ groundball profiles, and how did they compare to other clubs? To that end, I took year-to-year GB% changes of pitchers who changed teams following the 2012–2014 seasons, weighed them by the delta method (by way of harmonic means), and credited the differences to acquiring teams.

CHANGE IN TEAM-SWITCHERS GB RATES (2013–2015) Subset League Average GB% Y2Y Change Pirates GB% Y2Y Change Pirates Sample Size League Rank of Pirates’ Boost Actual GB% +0.1% +5.1% 2,071 1 Predicted GB% (on BIP) -0.5% +4.8% 2,071 3 Predicted GB% (all pitches) -0.3% +2.4% 10,999 3

In the past three full years, no team’s new pitchers lifted their groundball percentage on balls in play quite like new Pirates did, who tacked an extra five percent onto their collective rate. At +2.4 percent, their “all-pitch” boost was also very high. We can break that last subset down by pitch type and see the extent to which predicted groundball rates rose for new arrivals’ specific pitches.

CHANGE IN PREDICTED GB% FOR TEAM-SWITCHERS’ PITCH TYPES (2013–2015) Subset League Average GB% Y2Y Change Pirates GB% Y2Y Change Pirates Sample Size League Rank of Pirates’ Boost Fastball -0.3% +2.1% 7,921 5 Offspeed -0.7% +1.2% 4,301 7 Breaking -0.3% +3.7% 1,722 2

That new Pirates pitchers threw more groundball-friendly fastballs is no surprise given how the team has transitioned pitchers away from four-seamers and to sinkers. What I didn’t expect is that Pirates pitchers’ breaking balls became even more groundball-friendly than the heat. Primarily, their breaking balls changed by being located farther outside (by 1.5 inches) and having added velocity (+0.5 mph), changes that ranked them third and ninth among the 30 teams.

Does this mean a pitcher who is signed by the Pirates can expect his overall groundball percentage to rise by 5.1 percent, his fastball groundball percentage to rise 2.1 percent, and so on? No, we can’t take that leap and make that conclusion. That’s because the Pirates handpicked specific pitchers who were strong candidates to have their groundball percentage amplified. Not just any MLB pitcher will benefit from this tutelage, and this year the Pirates seem to have picked up several pieces that don’t quite fit.

New arrival Juan Nicasio has always had suspect command. In spring training, he worked with pitching coach Ray Searage to pitch lower in the zone. Despite some March success, he has ended up throwing many pitches in the fat part of the zone. That’s bad for grounders, and Nicasio loses further margin for error due to his arsenal, which features a straight fastball and slider, but not a sinker or changeup that he can lean on. The former Rockie has been even more of a flyball-oriented pitcher in 2016.

Also, Searage directed free agent signee Ryan Vogelsong to pitch inside more, and the veteran has done so against righties. But, again—yesterday’s models show this does little to generate extra grounders, and sure enough, Vogelsong’s groundball percentage hasn’t improved. Even apart from BIP ratios, neither acquisition has pitched well, either. In all, the 2016 Buccos’ groundball percentage has dropped by 3.7 percent since last year, and at 46.7 percent, it’s just 1.5 percent better than league average.

If the Pirates aimed to raise the groundball rates of the flyball-heavy pitchers who joined the staff this past offseason, they haven’t (yet) succeeded. Also possible is that grounders weren’t a priority for these acquisitions, but Pittsburgh still signed them as good buy-low opportunities. Either way, we would be seeing a change from a team that spent three years bringing players in and making them into groundball-friendly pitchers. And it will be interesting to see how far they deviate from the formula that jump-started their renaissance in the first place.