Francisco Lindor is a Legit Power Threat

It isn’t a secret. Francisco Lindor is a phenomenal baseball player. Whether it’s making an amazing play at shortstop, generating great contact, or even drawing a walk, Francisco Lindor is drawing the attention of baseball fans.

Francisco Lindor has never been thought of as a power hitter. He doesn’t appear as one either, standing at 5-11, 190 lbs. Here’s what ESPN Prospect Writer, Keith Law had to say.

 
“Lindor doesn't look like a power hitter but has exceptional lower-half strength and his swing will allow him to eventually get to that power even though he doesn't finish with a ton of loft. Even at 12-15 homers, which is probably a neutral projection for him, he'll be an All-Star thanks to grade-70 defense and OBPs up near .400 with plenty of doubles and 20-plus steals a year.”

And John Sickels of Minor League Ball.

 
That's in the short term. In the long term, I suspect that Lindor can develop into a better hitter than most people currently expect. I like his swing. He makes easy contact, controls the strike zone reasonably well, and should grow into more gap power as he matures physically. He isn't going to be a 20-homer guy, but it wouldn't surprise me at all to see him hit 10-15 homers per season at maturity, with a respectable number of doubles and above-average batting averages and OBPs. Add that to his defense and you'll have a helluva player by the time he's in his mid-20s.

This was a reasonable statement too. Many viewed Lindor as an all-around, good baseball player. Great plate discipline, switch hitter, great glove, great baserunning, etc. Many also believed there was power in that small frame. And like Keith Law said, the strength in his lower body was capable of spraying the ball all over the field with a line drive approach. 12-15 homers was a foreseeable amount for him, an amount most teams would take for one of their middle infielders.

But maybe there is more.

Ball in the Air

To get an overall understanding of Lindor’s tendencies, let’s rewind back to his rookie year in 2015. That year, Lindor posted a vertical angle of 4.5, well below the major league average of 10.5 that year.

Not surprisingly, these numbers led to a very above-average 50.8% groundball rate.  But with his great speed, this was a good thing. Out of 252 batters that hit at least 100 groundballs in 2015, Lindor ranked second in BABIP at .337. Though, this did hurt his power game, as his xSLG was at .432 in 2015.

Lindor then made some improvements in 2016, posting a vertical angle of 9.3, more than doubling the number from the previous year. In doing so, he was making better contact, increasing his exit velocity, average batted ball distance, and line drive percentage.

With this, we started to see some power.  In 2016, he hit 19 home runs, with xStats tabbing him at 15.4.

Looking back at Lindor’s average launch angle by month, I noticed something. In September Lindor posted the highest launch angle of his career by a decent margin, coming in at 13.9. But the results weren’t showing. From the looks of it, Lindor was struggling to make good contact posting the highest PH% of his career.

Results

Now, if you’ve seen Francisco Lindor in so far this, it’s scary. He’s on pace to have the best month of his career by far. It looks like he’ll have the highest xSLG, xOBA, and xOBA+ in any month of his career.

And this all because of a drastic change in his launch angle.

Like I said, Lindor had the highest launch angle of his career by a decent margin last September. Well, this April has been a different world. Lindor has had a launch angle of 17.3 so far this year. And guess what, that isn’t even his biggest change.

Lindor is swinging the bat faster. On well strick balls (21 to 36), he is swinging the bat 68.2 MPH, well above his career average.

Put this all together, what do you get? More homers! Lindor is leading all of the majors in xHRs, at 6.7. Next closest is Khris Davis at 5.9. He’s second among qualified hitters in xSLG.

Conclusion

This power streak by Lindor might be here to stay. As long is keeps digging the bat downwards, his lower body strength and quick swing (ranks 2nd in swing speed with launch angle of 21 to 36) will generate some serious pop for a middle infielder.

Lindor’s power might be heading more in the territory of someone like Carlos Correa or Corey Seager. He might not have quite the pop of some of the elite power shortstops, but he’s trending there.

And if this is for real, Francisco Lindor might be on a path that leads him to Cooperstown.

xStats and Fantasy Uses for Statcast

This is the most up to date article about xStats. It describes the current methodology and the descriptive and predictive qualities of the stats. It also delves into a quick and dirty method for adjusting the stats using a histogram of their exit velocities.

This article was featured on the Hardball Times on March 9th, 2017, and it is even John Sickels Approved. I consider it a must read for anyone even tangentially interested in xStats or Statcast in general.

Introducing xFantasy Parts I, II, III, and IV.

xFantasy is a system based on xStats that integrates hitters' xAVG, xOBP, and xISO in order to predict expected fantasy production (HR, R, RBI, SB, AVG). The underlying models are put together into an embedded "Triple Slash Converter" in Part 2. Part 3 compares the predictive value of xFantasy (and therefore xStats) vs. Steamer and historic stats, ultimately finding that for players under 26, xStats are indeed more predictive than Steamer.

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Fitting Running Speed into xOBA and xBABIP.

A general introduction to the methods I use to incorporate running speed.  The system remains almost entirely intact, but I have since added a few small corrections here and there to fix small problems.  I'm not happy with this system, and I would love to get rid of it, but I haven't found a better solution.  Which is a low bar, since I don't feel this solution is very good.

xOBA and Using Statcast Data To Measure Offense

The first public introduction to xStats. Some of the methods described here are obsolete, but the core concepts remain intact.  Keep in mind that the window and bucket system has been updated to more resemble a kernel based approach; park factors and handedness factors were added; and exit velocities are modified and corrected for measurement error.