Author Archive

Team Ball-in-Play Analysis: NL Central

Rejuvenated by a week away from baseball altogether, I’m back with the last in a series of articles on team ball-in-play profiles. In the last installment, we examined the AL Central. We’ve saved the best — well, at least the division with the best team — for last, as we take a look at the NL Central. As we have previously, we’ll use granular data such as plate-appearance frequencies and BIP exit speed/angle as of the All-Star break to project “true-talent” club records.

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Team Ball-in-Play Analysis: AL Central

Our series of divisional team BIP analyses rolls on. Most recently, we examined the NL East. Today, the AL Central. We’ll use granular data such as plate-appearance frequencies and BIP exit speed/angle as of the All-Star break to project “true-talent” club records.

About 90 games’ worth of balls in play is a fairly substantial sample size, one that enables us to make fairly educated guesses about the true-talent level of each team. We’ll compare our projections to club’s actual records at the break, examining the reasons for material variation along the way. Read the rest of this entry »


Team Ball-In-Play Analysis: NL East

We’re now more than halfway through our division-by-division look at granular team ball-in-play data, as of the All Star break. Today, we take a macro-type view of the plate-appearance frequency and BIP exit speed/angle detail for NL East clubs.

About 90 games’ worth of balls in play is a fairly substantial sample size, one that enables us to make fairly educated guesses about the true talent level of each team. Let’s use this information to project true-talent team won-lost records and compare them to their actual marks at the break, examining the reasons for material variation along the way. Read the rest of this entry »


Team Ball-in-Play Analysis: AL East

Welcome to the third installment of our division-by-division look at team ball-in-play profiles, based on data accumulated through the All-Star break. In the first two pieces, we identified the Seattle Mariners and Los Angeles Dodgers as the best “true-talent” clubs in their respective divisions; their recent surges couldn’t have been timed better. Today, we take a macro-type view of the plate-appearance frequency and BIP exit speed/angle detail for AL East clubs.

About 90 games’ worth of balls in play is a fairly substantial sample size, one that enables us to make fairly educated guesses about the true talent level of each team. Let’s use this information to project true-talent team won-lost records and compare them to their actual marks at the break, examining the reasons for material variation along the way. Read the rest of this entry »


Team Ball-in-Play Analysis: NL West

Today, our analysis of granular team ball-in-play data continues. Last time, we examined AL West clubs. Today, we take a macro-type view of the plate appearance frequency and BIP exit speed/angle detail for NL West clubs.

About 90 games’ worth of balls in play is a fairly substantial sample size, one that enables us to make fairly educated guesses about the true talent level of each team. Let’s use this information to project true-talent team won-lost records and compare them to their actual marks at the break, examining the reasons for material variation along the way. Read the rest of this entry »


Team Ball-in-Play Analysis: AL West

Over the last few weeks we have taken a position-by-position look at ball-in-play data for both hitters and pitchers, assessing their respective contact quality/management ability. Next up: a macro-type evaluation of overall team performance in those areas. An overview of this series appeared in this space last week.

Over the next few weeks, we’ll take a division-by-division look at each team’s granular data through the All-Star break, ultimately comparing their actual won-lost records to projected ones based on exit speed/angle of every ball in play hit and allowed by each club. About 90 games’ worth of balls in play is a fairly substantial sample size, one that enables us to make fairly educated guesses about the true talent level of each team. Today, we’ll begin to drill deeper into the data.

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Team Ball-in-Play Analysis: An Overview

Over the last few weeks we have taken a position-by-position look at granular ball-in-play data for both hitters and pitchers, assessing their respective contact quality/management ability. Next up: a macro-type evaluation of overall team performance in those areas.

Over the next few weeks, we’ll take a division-by-division look at each team’s granular data through the All-Star break, ultimately comparing their actual won-lost records to projected ones based on exit speed/angle of every ball in play hit and allowed by each club. About 90 games’ worth of balls in play is a fairly substantial sample size, one that enables us to make fairly educated guesses about the true talent level of each team. Today, we’ll focus on a brief overview of general BIP data estimating the overall hitting, pitching and defensive abilities of all 30 clubs; we’ll drill deeper into the data in the subsequent divisional articles.

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Pitcher Contact-Management Update: New Qualifiers

A few weeks back, we took a look at the 2016 contact-management performance of qualifying pitchers in both leagues. Since then, a number of new qualifiers have emerged. Today, we’ll utilize tools such as plate-appearance-outcome frequencies, exit-speed and launch-angle allowed to see how these hurlers have performed in this vital area.

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Hitter Contact-Quality Report: New Qualifiers

Over the last few weeks in this space, we’ve been evaluating regular position players’ contact quality utilizing granular data such as plate appearance outcome frequencies, exit speed and launch angle. (Catchers represented the last installment in that series.) Over that time, players not included in our original analysis have overtaken previous incumbents in terms of total plate appearances. Today, we’ll add players who did so as of July 4 to the mix. Next time, we’ll look at newly qualified pitchers.

The data examined today runs through July 4. Players are separated by league, and are listed in Adjusted Production order. Adjusted Production expresses, on a scale where 100 equals average, what a hitter “should have” produced based on the exit speed/launch angle of each ball put in play. Each player’s Adjusted Contact Score, which weeds out the strikeouts and walks and states what each player should have produced on BIP alone, is also listed. Here goes:

AL Adds’ BIP Profiles
Name Avg MPH FLY MPH LD MPH GB MPH POP% FLY% LD% GB% ADJ C K% BB% wRC+ ADJ PR Pull%
Grossman 87.4 88.0 87.3 86.6 0.0% 39.0% 23.0% 38.0% 113 22.2% 18.1% 142 124 39.2%
Forsythe 91.9 92.3 95.0 89.2 1.9% 29.8% 25.5% 42.9% 126 21.6% 7.4% 129 114 34.8%
Hardy 93.1 91.1 98.3 94.6 4.9% 32.5% 19.5% 43.1% 86 13.3% 4.7% 67 93 47.2%
Merrifield 89.2 92.5 90.2 87.0 0.0% 24.2% 28.8% 47.0% 102 21.3% 2.8% 95 86 34.1%
Barney 87.0 89.8 88.8 84.4 3.5% 25.9% 23.1% 47.6% 75 14.6% 7.0% 96 84 38.2%
Gattis 89.2 88.7 92.6 89.6 5.1% 33.8% 15.9% 45.2% 91 23.7% 8.5% 82 84 48.4%
Buxton 89.8 86.5 93.3 90.7 7.4% 35.8% 23.5% 33.3% 81 39.4% 3.9% 48 43 43.7%

Most of the column headers are self-explanatory, including average BIP speed (overall and by BIP type), BIP type frequency, K and BB rates, wRC+ and Adjusted Production, which incorporates the exit speed/angle data. Each hitter’s Adjusted Contact Score (ADJ C) is also listed. Adjusted Contact Score applies league-average production to each hitter’s individual actual BIP type and velocity mix, and compares it to league average of 100.

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Hitter Contact-Quality Report: Catcher

The All-Star Game is behind us, the unofficial second half of the season is set to kick off and, today, we present the last installment in our position-by-position look at hitter contact quality. Last time, it was right fielders; this time, catchers. Granular ball-in-play data such as BIP frequencies, exit speed and launch angle are the key inputs in this analysis.

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Hitter Contact-Quality Report: Right Field

The All-Star break is beckoning as we come down the homestretch of our position-by-position look at hitter contact quality. We will again use granular ball-in-play data such as BIP frequencies, exit speed and launch angle to perform the analysis. Two positions to go. Last time, it was center fielders; today, it’s the right fielders’ turn.

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Hitter Contact-Quality Report: Center Field

With the extended holiday weekend behind us, we get back to the business at hand: our position-by-position look at hitter contact quality. Only three positions to go. Last time, it was left fielders. This time: a fun-filled group of center fielders. As we have in the previous installments, we’ll use granular ball-in-play data, such as BIP type frequencies, exit speed and launch angle to perform this analysis.

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Hitter Contact-Quality Report: Left Field

Our position-by-position review of contact quality grinds on. In the last installment, we examined third basemen. Today, we move into the outfield. It’s two starkly different stories with regard to left-field production, as National League regulars have dramatically out-produced their junior circuit counterparts. As we have in the previous installments, we’ll use granular ball-in-play data, such as BIP type frequencies, exit speed and launch angle to perform this analysis.

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Hitter Contact-Quality Report: Third Base

Our position-by-position tour of hitter contact quality reaches its midway point today. Last time, we looked at shortstops. Today, hot-corner regulars. As we have in the previous installments, we’ll use granular ball-in-play data, such as BIP type frequencies, exit speed and launch angle to perform this analysis.

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Hitter Contact-Quality Report: Shortstop

The winter sports have crowned their champions, Cleveland has its first title in eons thanks to their prodigal son LeBron, and baseball now owns a greater part of the sporting stage for the rest of the summer. In that spirit, we continue to take a position-by-position look at hitter contact quality, utilizing granular ball-in-play data, such as BIP type frequencies, exit speed and launch angle. Last time, it was second basemen. Today, the shortstops are at bat. Read the rest of this entry »


Hitter Contact-Quality Report: Second Base

Earlier this week, we began a position-by-position look at hitter contact quality with a review of the first-base and DH population. Today, we continue to use granular ball-in-play data, such as BIP type frequencies, exit speed and launch angle, to review second basemen.

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Hitter Contact-Quality Report: First Base and DH

Over the last couple of weeks, we’ve taken a look at the 2016 contact management ability of ERA-qualifying starting pitchers in both leagues, utilizing granular batted-ball data. Now it’s the hitters’ turn. Over the next few weeks, we’ll take a position-by-position look at hitters’ contact quality, using exit speed, launch angle, and BIP type frequencies as our tools. Today, let’s look at each team’s primary first basemen and designated hitters.

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American League Contact-Management Update

Starting pitchers get the job done in various ways; some excel at bat-missing and/or command. Others are more adept at managing contact on balls in play. The very best are able to clear the bar in all three areas. Sample sizes for the 2016 season have increased in size to the point that we actually should begin paying attention. Last week, we checked in with NL ERA qualifiers regarding their early-season contact-management performance; this week, it’s the AL’s turn.

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National League Contact-Management Update

Another page has been ripped off of the calendar, and sample sizes are finally getting to a point where they actually matter. This, then, represents a good occasion to take a first look at starting-pitcher contact-management trends. Today, it’s the National League.

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The 2016 Single-Game Pitching Belt: Kershaw vs. Velasquez

Earlier this week, we again utilized granular batted-ball data to determine whether Vince Velasquez could hold onto the championship belt for the best single-game pitching performance of the season. He did so, beating out Max Scherzer‘s 20-strikeout performance. To this point, we’ve also matched the Phils’ righthander against Jaime Garcia‘s one-hitter and Jake Arrieta‘s no-hitter.

When one is discussing pitching excellence, it’s only a matter of time before Clayton Kershaw enters the discussion. Today, let’s match up Velasquez’16 K, 0 BB vanquishing of the Padres on April 14 to, well, Kershaw’s entire body of 2016 work.

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