The major awards have been handed out, qualifying offers have been accepted and rejected, and free-agent signings and trades have begun to trickle in. Let’s continue our look backward at the 2016 season in an effort to look forward. After reviewing AL first basemen and designated hitters, we continue our look at position-player performance utilizing granular exit-speed and launch-angle data with NL first basemen.
The 2016 season is in the books, and the Hot Stove is already heating up big time. Over the last week or so, we’ve used granular data to evaluate the performance of qualifying starting pitchers in both leagues. Today, we begin to turn our head toward the position players.
The GM Meetings are in progress, and another offseason of frantic player movement seems about to begin in earnest. In the meantime, let’s continue our offseason series of granular BIP-based player performance evaluation.
Earlier this week, we used exit speed and launch angle data to analyze how ERA-qualifying AL starting pitchers “should have” performed in 2016. Today, we take a similar look at qualifying NL starters.
A thrilling season and postseason is in the books, and another whirlwind offseason is ready to be set in motion. This would appear to be a good time to take one last look back at 2016 player performance, utilizing granular data to assess pitcher and position-player true-talent levels.
In the coming weeks, we’ll use exit-speed and launch-angle data to show what pitchers and position players “should have” done this season. Starting pitchers are first in the barrel; today, we’ll take a look at AL ERA qualifiers.
One day, when we look back upon the 2016 postseason, mostly positive memories will be evoked. The end of longstanding World Series droughts for both combatants, the Cleveland Indians and Chicago Cubs, culminating in a classic seven-game battle. The underdog Indians laying waste to the remainder of the AL field. The heavily favored Cubs scrapping to get past both the Dodgers and the Giants. The emergence of Francisco Lindor, Corey Kluber, Kris Bryant, Addison Russell and others on the postseason stage, etc.
Let’s not kid ourselves, however, regarding the enduring legacy of this postseason; it will be Andrew Miller, Aroldis Chapman, Kenley Jansen, and yes, Zach Britton, and the way they were used, and not used. It will be the way that one of the underpinnings of modern sabermetric thought busted into the mainstream in a big way: the postseason that ace relievers, not “closers” per se, became used more more optimally, in “game” situations rather than merely “save” situations.
The Fall Classic is underway, with the underdog Cleveland Indians landing the first haymaker blow for their third series in a row. The NL Champion Chicago Cubs were clearly the best team in baseball throughout the regular season; will they be able to do what the Tribe’s previous postseason opponents couldn’t, and fight their way off of the ropes and onto ultimate victory?
This week, we’re taking a macro, ball-in-play-oriented look at each team and its key players. Earlier this week, we looked at the AL champs; today, it’s the Cubs’ turn under the microscope, as we examine granular data such as BIP frequencies, exit speeds and launch angles to get a feel for what made them tick in 2016.
There’s a chill in the air, as Halloween and the long winter that follows have begun to beckon for those of us who make their home in the Midwest. This is a special fall season for many Midwesterners, as someone’s long regional nightmare is about to end: either the Indians or Cubs are going to win the World Series for the first time since either Truman beat Dewey, or Taft beat Bryan.
This week, let’s take a macro, ball-in-play-oriented look at each team and its key players. Today, it’s the AL champs in the barrel, as we examine granular data such as BIP frequencies, exit speeds and launch angles to get a feel for what made the Indians tick in 2016.
The playoffs roll on, with subplots galore, most of them involving pitching-staff usage patterns that are long overdue. Meanwhile, let’s conclude our two-part series examining macro team BIP data for the 10 playoff teams, broken down by exit speed and launch angles. (Read the Part 1 here.) We’ll examine what made these teams tick during the regular season and allowed them to play meaningful October baseball. It’s more or less a DNA analysis of the clubs that made it to the game’s second season.
First, some ground rules. For each club, all offensive and defensive batted balls were broken down (first) by type and (second) by exit speed. Not all batted balls generated exit speed and/or launch angle data; just over 14% were unread, most of them weakly hit balls at very high or low launch angles. How do we know this? Well, hitters batted .161 AVG-.213 SLG on them, a pretty strong clue.
BIP types do not strictly match up with FanGraphs classifications. For purposes of this exercise, any batted ball with a launch angle of over 50 degrees is considered a pop up, between 20 and 50 degrees is a fly ball, between 5 and 20 degrees is a line drive, and below 5 degrees is a ground ball. For background purposes, here are the outcomes by major-league hitters for each of those BIP types: .019 AVG-.027 SLG on pop ups (5.7% of measured BIP), .326 AVG-.887 SLG on fly balls (30.9%), .658 AVG-.870 SLG on liners (24.4%) and .238 AVG-.260 SLG on grounders (39.1%).
As you might expect, there are massive differences in production within BIP types based on relative exit speed. If you hit a fly ball over 100 mph, you’re golden, batting .766 AVG-2.739 SLG. If you drag that category’s lower boundary down just 5 mph, however, you get to the top of the donut hole, where fly balls go to die. Hitters batted just .114 AVG-.209 SLG on fly balls between 75-95 mph. All other fly balls — yes, even including those hit under 75 mph — fared much better, generating .387 AVG-.786 production.
Line drives tend to be base hits at almost all exit speeds. All the way down to 75 mph, hitters bat over .600 on batted balls in the line-drive launch-angle ranges; down to 65 mph, hitters still bat around .400 range in each velocity bucket. At 65 mph and higher, a liner generates an average .673 AVG-.889 SLG line. Under 65 mph, liners tend to land in infielders’ gloves; hitters batted just .170 AVG-.194 SLG on those. On the ground, hitters batted a strong .423 AVG-.456 SLG on grounders hit at 100 mph or higher. Under 85 mph, however, the hits dry up almost totally, with hitters producing a .107 AVG and .117 SLG. Between 85-100 mph, hitters bat closer to the overall grounder norm, at .267 AVG-.294 SLG.
With that as a backdrop, let’s conclude our look at each playoff club’s offensive and defensive BIP profiles. Last time, we profiled the Orioles, Red Sox, Cubs, Indians and Dodgers; today, we’ll look at the other five, in alphabetical order:
New York Mets
Two of the 10 playoff teams played well over their true talent this season, at least based on my BIP-centric method of team evaluation. Both will be covered today. First, the Mets hit significantly more pop ups than their opponents (+69), not including untracked ones in that 14% “null” group. On the positive side, the Mets hit 160 more fly balls than their opponents; they were a whopping +86 vis-à-vis their opponents in the 95-105 mph buckets. This explains why they hit 66 more homers than their opponents.
Over time, teams take on the characteristics of some of their key players in the minds of analysts and fans. The Rays are eternally linked with Evan Longoria, known for power taking precedence at the plate, with a focus on defense. Similarly, Ryan Braun is the poster child for the Brewers, a bat-oriented player without a material defensive presence.
This week and next, let’s allow the players themselves to fade into the background, and draw some conclusions from a simple set of numbers — namely, each of the 10 playoff clubs’ team ball-in-play (BIP) statistics, broken down by exit speed and launch angles. We’ll examine what made these teams tick during the regular season and allowed them to play meaningful October baseball.
Zach Britton has recently found himself at the forefront of baseball consciousness for a lot reasons, mostly positive, some negative, albeit through no fault of his own. He had a supremely excellent season in a tightly tailored, typical closer’s role for the Orioles, and his non-usage in last week’s wild-card game has almost become a caricature, a metaphor for outdated laissez-faire managerial strategies.
He will certainly receive many, many Cy Young votes, and might even walk off with the award. In my piece here last week, I compared his 2016 performance to some of the top seasons produced by AL starters, utilizing granular batted-ball data, and found that, while Britton does at least belong in the conversation, he didn’t deliver as much production to his club, in a year that is admittedly without a runaway choice among starting pitchers. What if I told you, however, that Britton didn’t even have the best season among AL relief pitchers?