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Thursday, May 18, 2017

Twins Miguel Sano is 2017’s hardest hitter | MLB.com

Highest percentage of batted balls hit 95 mph or harder in 2017
68.3 percent—Sano, Twins
58.9 percent—Miguel Cabrera, Tigers
58.0 percent—Khris Davis, A’s
57.6 percent—Joey Gallo, Rangers
55.5 percent—Nicholas Castellanos, Tigers
54.6 percent—Manny Machado, Orioles
52.9 percent—Ryan Zimmerman, Nationals
51.3 percent—Aaron Judge, Yankees
51.3 percent—Matt Carpenter, Cardinals
51.0 percent—Justin Bour, Marlins
Minimum 50 balls in play. MLB average—33.5 percent

Jim Furtado Posted: May 18, 2017 at 10:50 AM | 7 comment(s)
  Beats: statcast

Wednesday, May 17, 2017

How Catch Probability works for diving catches | MLB.com

I need to look up Jackie Bradley on the Statcast fielding thingie.

Jim Furtado Posted: May 17, 2017 at 10:48 AM | 1 comment(s)
  Beats: fielding, statcast

How to Beat Statcast’s Hitting Metric | FanGraphs Baseball

At first glance, the relationship doesn’t appear to be particularly strong. To receive an r-squared of .27, however, between two stats that wouldn’t seemingly have a lot to do with each other, suggests that there’s something to this idea. Of the 28 batters above who recorded at least five runs on the bases over the last two years, all but one produced a positive xwOBA-wOBA. That one outlier is Gregory Polanco and his xwOBA-wOBA was .001. Those good baserunners, on average, beat their xwOBAs by 22 points per season in 2015 and 2016. The remaining players beat their xwOBA by an average of just two points per season in those years. At the very bottom, the 10 worst baserunners averaged a 15-point surplus in xwOBA compared to wOBA. The effect among slower players appears to be minimal when it comes to determining whether posting high xWOBAs (relative to observed wOBA) is some sort of skill. For the most part, it seems to have little to do with skill. So, in others words, if you see a player underperforming his xwOBA, it would seem that bad luck actually is involved.

On the other hand, if a player is posting an xwOBA lower than his wOBA, we can’t immediately jump to the conclusion that there’s a lot of good luck involved. Speed is a skill which has been stripped out of xwOBA. If a player can run out a lot of infield singles, that’s going to show up in wOBA, but not in xwOBA. If a player can turn a bunch of singles into doubles, that’s going to factor into wOBA, but not xwOBA. This doesn’t really discount xwOBA’s utility: after all, wOBA and wRC+ are fairly comprehensive offensive statistics, and they don’t account for a player’s offense once he reaches base. In addition, it still should be possible to identify players who have had good and bad luck simply by mentally compensating for speed a little bit. There should be a ton of great uses for xwOBA and we will get to more later, but we should keep in mind that players can beat xwOBA with their legs.

Jim Furtado Posted: May 17, 2017 at 10:37 AM | 0 comment(s)
  Beats: sabermetrics, statcast

Tuesday, May 16, 2017

The Twins defense is propping up a staggering pitching staff - Twinkie Town

An interesting comparison using Catch Probability. (Cubs fans should pass by this link.)

Jim Furtado Posted: May 16, 2017 at 11:58 AM | 0 comment(s)
  Beats: statcast, twins

Friday, May 12, 2017

New crop of sluggers head HR leaderboard | MLB.com

Yes, Yonder Alonso.

Jim Furtado Posted: May 12, 2017 at 11:57 AM | 10 comment(s)
  Beats: dingers, statcast

Monday, May 01, 2017


Aprils best Statcast Catch Probability catches | MLB.com

These catches are pretty, pretty good.

Jim Furtado Posted: May 01, 2017 at 09:55 AM | 2 comment(s)
  Beats: defensive plays, statcast

Thursday, April 27, 2017

Mariners’ James Paxton rising to ace status | MLB.com

Giddy up!

How overpowering has Paxton been? Coming into the game, his average four-seamer velocity of 95.8 mph ranked third out of the 56 pitchers in MLB with at least 150 four-seamers thrown, behind only right-handers Luis Severino of the Yankees and Gerrit Cole of the Pirates. He was even better Wednesday, averaging 96.2 mph with a high of 98.1, according to Statcast™.

Paxton relied on the four-seamer more heavily, throwing it for 74 of his 103 pitches (72 percent), compared with his average of 61 percent in his first four starts.

Jim Furtado Posted: April 27, 2017 at 06:46 AM | 0 comment(s)
  Beats: james paxton, mariners, statcast

Wednesday, April 19, 2017

Do MLB Teams Undervalue Defense — Or Just Value It Differently? | FiveThirtyEight

Whether because of Statcast or scouting, the Cubs and now the Cardinals have seen something in Fowler’s performance that current fielding valuations don’t seem to capture. And when two of the smartest front offices in baseball appear to be discarding defensive metrics, it makes you stop and wonder whether the metrics might just be wrong.

Jim Furtado Posted: April 19, 2017 at 08:38 AM | 19 comment(s)
  Beats: analytics, defense, sabermetrics, statcast

Tuesday, April 18, 2017

Statcast introduces new sprint speed metric | MLB.com

Top 2016 Sprint Speed by outfielders
29.8 feet per second—Hamilton
29.7 feet per second—Buxton
29.1 feet per second—Lorenzo Cain
29.0 feet per second—Paulo Orlando
28.7 feet per second—Jake Marisnick
28.6 feet per second—Gregory Polanco / Travis Jankowski / Max Kepler
28.3 feet per second—Christian Yelich
28.2 feet per second—Kevin Kiermaier

Jim Furtado Posted: April 18, 2017 at 10:48 AM | 11 comment(s)
  Beats: statcast

Saturday, April 01, 2017

Statcast 2017 preview for all 30 MLB teams | MLB.com

This is no prank. Statcast articles for every team for all my friends.

Jim Furtado Posted: April 01, 2017 at 09:12 AM | 0 comment(s)
  Beats: statcast

Friday, March 31, 2017

Statcast ranking of top defensive outfielders | MLB.com

More great stuff.

Jim Furtado Posted: March 31, 2017 at 08:43 AM | 27 comment(s)
  Beats: fielding, statcast

Wednesday, March 29, 2017

Statcast says Miguel Cabrera may be underrated | MLB.com

More great Statcast stuff.

Jim Furtado Posted: March 29, 2017 at 06:51 AM | 16 comment(s)
  Beats: miguel cabrera, statcast

Saturday, March 25, 2017

Dodgers’ pitchers rate well in Statcast metric | MLB.com

Lowest estimated OPS in 2016
.438—Kenley Jansen, Dodgers
.450—Andrew Miller, Yankees/Indians
.456—Zach Britton, Orioles
.471—Grant Dayton, Dodgers
.487—Aroldis Chapman, Yankees/Cubs
.491—Alex Reyes, Cardinals
.508—Shawn Kelley, Nationals
.515—Dellin Betances, Yankees
.517—Kershaw, Dodgers
.526—Seung Hwan Oh, Cardinals

Jim Furtado Posted: March 25, 2017 at 08:48 AM | 5 comment(s)
  Beats: dodgers, statcast

Tuesday, March 21, 2017

Outfield Defense: Does the Team Make the Player or Does the Player Make the Team?

A look at team outfield defense using Statcast.

Jason Heyward’s impact on the defending champion Cubs is clearly present through these numbers, but did not necessarily make his center field neighbor a better defender. But perhaps the difference in left fielder made an impact, in the other direction, on Dexter Fowler as well.
In Baltimore, Adam Jones performed worse when partnered with Mark Trumbo. However, other components may be at play — like Jones’ age curve.

Jim Furtado Posted: March 21, 2017 at 06:48 AM | 0 comment(s)
  Beats: statcast

Saturday, March 18, 2017

Rays, Reds lead Statcast outfield highlights | MLB.com

If you like great catches, Statcast has found some of the best.

Jim Furtado Posted: March 18, 2017 at 08:19 AM | 0 comment(s)
  Beats: statcast

Wednesday, March 15, 2017

Statcast’s New Defensive Metrics and Seattle’s Glove-First Outfield | U.S.S. Mariner

. I used his averages and calculated plays made above average for each player in 2015 and 2016, and then I looked at how their chances were distributed. That is, some players (Jackie Bradley, Jr.) saw proportionally more extremely difficult opportunities, while others (Kevin Kiermaier) saw fewer. The plays on the Statcast leaderboards apparently don’t include the absolutely never missed, can of corn, 100% probability balls. At least, that’s my guess just from noting that the sum of each players chances across all 5 buckets totals a fraction of their overall chances/putouts as reported elsewhere. If true, that means that the plays that really separate defenders are in a few not-terribly-large buckets in the ranges where catches are made 25-50% of the time or so. Given THAT, I’m pretty impressed with how reliable these numbers look. Kiermaier, Lorenzo Cain, Ender Inciarte, etc. look great both years despite varying playing time, opportunities, etc.

Jim Furtado Posted: March 15, 2017 at 06:12 AM | 3 comment(s)
  Beats: mariners, statcast

Tuesday, March 14, 2017

Let’s Play With New Defensive Data | FanGraphs Baseball

I’m not sure there’s a surprise in the bunch. Which is probably more of a good sign than a bad one — one wouldn’t think we’ve been completely wrong all this time. For as much as people have openly criticized the advanced defensive numbers, I think the bulk of the disagreement has centered on infield play, especially in the age of infielders moving around all over the place. We’ve long had a pretty good grasp on the outfield, I think. Statcast here mostly supports the information we already had. Kevin Kiermaier? Amazing! Billy Hamilton? Amazing! Keon Broxton? You better believe he’s amazing!

Maybe one way of interpreting this is as further evidence that Kiermaier has been better out there than Kevin Pillar. I know that’s been fiercely debated, but Statcast knows more than most of us do. There’s still room for these numbers to be adjusted, so Blue Jays fans can continue to take some heart. Travis Jankowski has apparently got it. Peter Bourjos has apparently still got it.

Jim Furtado Posted: March 14, 2017 at 02:56 PM | 2 comment(s)
  Beats: sabermetrics, statcast

Thursday, March 09, 2017

Billy Hamilton is a Statcast highlight reel | MLB.com

I’m not sure this is the right breakdown. As he said, “how can you make a great play if the opportunity to make a great play doesn’t exist first? Of those 116, 44 didn’t make a single Five-Star play.” Wouldn’t a better look be percentage of five-star catches in five-star opportunities be a better comparison?

For this sample, we’re looking at the 116 outfielders who had at least 100 total outfield chances and at least 10 Five-Star chances, because, after all, how can you make a great play if the opportunity to make a great play doesn’t exist first? Of those 116, 44 didn’t make a single Five-Star play.

Percentage of Five-Star plays made
38 percent—Hamilton
36 percent—Travis Jankowski
30 percent—Kevin Kiermaier
27 percent—Eaton / Scott Schebler
25 percent—Rajai Davis
24 percent—Inciarte / Byron Buxton / Lonnie Chisenhall

While this is a good proxy for great outfield defense, it’s also not the entire picture, either. Chisenhall, for example, did make a handful of outstanding plays—here he is robbing Starlin Castro on an 8 percent Catch Probability play in July—but he also made only a single Four-Star play, while Hamilton made 15. Schebler didn’t make any Three-Star plays, while Hamilton made 15 more of those, too. Like on offense, consistency matters.

Jim Furtado Posted: March 09, 2017 at 07:15 AM | 2 comment(s)
  Beats: statcast

Tuesday, March 07, 2017

Statcast’s impact on baseball has been considerable

Bring it on!

“[The dialogue change has happened] in some sense a little more quickly than I would have thought. Two years in baseball time is very little,” said Mike Petriello, an analyst for MLB.com who is in many ways the site’s voice of Statcast. “Exit velocity took off very quickly. It’s very easy to understand. It’s ubiquitous. You see it in a lot of in-stadium scoreboards now. You see guys talking about it constantly now. Kris Bryant talks about exit velocity and launch angle. Mark Trumbo has talked about his launch angle. … It’s informing the way the game is being talked about and also [how it’s being played] on the field.”

Jim Furtado Posted: March 07, 2017 at 03:37 PM | 0 comment(s)
  Beats: statcast

Fixing Batted-Ball Statistics with Statcast – The Hardball Times

Everything you wanted to know about line drivers but were afraid to ask.

Jim Furtado Posted: March 07, 2017 at 08:32 AM | 4 comment(s)
  Beats: sabermetrics, statcast

Monday, March 06, 2017

Statcast and the Future of WAR | FanGraphs Baseball

I’ve argued about this for 20 years. The MVP question and the best player question are two entirely different things. Using WAR for either conflates the two. Why not transform WAR into a purely contextual answer (value) and continue to define results in runs and wins based on outcome and then use Statcast probabilities as a scouting tool for the best player question? In my mind, using Statcast as the inputs on an improved 20/80 scouting scale and apportioning all the components properly would be a wonderful upgrade to what’s done now. It would also put teams on a better path for projections as they will be able to better quantify aging patterns in a more realistic way.

This tension between what happened, how it affected the scoreboard, and how much credit to give to players for things they don’t control is a difficult thing to resolve. And now that we’re getting even more granular metrics about a player’s contribution to outcomes, these questions are going to continue to be relevant. Knowing the guys at MLBAM on a personal level, I’m pretty comfortable with the fact that they’ll handle these questions thoughtfully, and if (or when?) they do produce an MLB.com WAR model, it will be with all of these questions answered as well as they feel they can.

But while Statcast holds a lot of promise for improving the pitching and defensive sides of the components, getting ever-more granular hitting data might force us to again ask what we want WAR to be, and what the goal of the model is. There is no obvious right answer here, and that’s one of the reasons there will always be multiple ways of calculating WAR.

Jim Furtado Posted: March 06, 2017 at 01:48 PM | 5 comment(s)
  Beats: statcast, war

Saturday, March 04, 2017

Statcast wants to change how we’re consuming baseball games

BAM wants anyone interested to understand from whence its WAR came. So the idea is for a tree – one that allows a click or tap on the overall number, which then branches into components (offensive, defensive, baserunning, etc.) that show his overall value in each. From there comes a breakdown of more subcategories, and subs of subs, and on until piecing together WAR isn’t so daunting.

They’re also toying with the idea of an alternative presentation for their WAR. Even though the current one correlates quite strongly with overall victories in a season when adding up individual WAR contributions from each team, BAM’s audience is different than the B-R/FanGraphs niche. BAM could, for example, judge players on a 1-to-100 scale using the same criteria as another would for WAR.

“There’s an argument to be made for putting out an extra scale,” Petriello said.

“What will make our version of WAR intriguing,” Willman said, “is the way we’re going to make it accessible.”

Not just with WAR, Tango said, but all of Statcast: “We’re in the third inning.”

RoyalsRetro (AG#1F) Posted: March 04, 2017 at 01:59 PM | 23 comment(s)
  Beats: mlbam, statcast

Saturday, February 18, 2017

Mets top 2017 Statcast fastball velocity ranks | MLB.com

Mets, Mets, Mets.

Jim Furtado Posted: February 18, 2017 at 07:52 AM | 3 comment(s)
  Beats: mets, statcast

Sunday, February 12, 2017

Twins project for strongest 2017 outfield arms | MLB.com

More wonderful Statcast stuff.

So the way we’ve identified “competitive throws” is to identify a player’s 90th percentile arm strength, and then take the average of all throws above the 90th percentile, as a good proxy for tracking only throws where a fielder was trying to make play with some urgency. Of the 107 outfielders who had at least 10 such throws last year, Aaron Hicks’ average of 99.4 mph was baseball’s best (remember this?), and Khris Davis’ average of 72.5 mph was the weakest. That’s a big gap, yet it passes the eye test.

Jim Furtado Posted: February 12, 2017 at 07:00 AM | 0 comment(s)
  Beats: defense, statcast

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