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 »

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 »

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.

Read the rest of this entry »

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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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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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:

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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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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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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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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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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