Dataset Information

Does the combination of different pitches and the absence of pitch type information influence timing control during batting in baseball?

ABSTRACT: Baseball pitchers use various pitch types to reduce hitting accuracy, but little is understood of the practical strategy of using visuomotor skills and timing control to respond to different pitches. This study examined 1) effectiveness of pitch type combinations, and 2) relationship between the presence and absence of advance information about the next pitch and the timing error. Twenty-six high school baseball players hit a ball launched from a pitching machine in a combination of fastballs (34.3±1.3 m·s-1), curveballs (25.4±1.0 m·s-1), and slowballs (25.5±0.9 m·s-1). Each participant performed three conditions. (1) Continuity condition (15 trials), in which the same pitch type was thrown five times consecutively. (2) Random condition (30 trials), in which pitch type was not preliminarily conveyed to the participants. (3) Open condition (20 trials), in which the next pitch type was preliminarily conveyed to participants. Participants' hitting movement was recorded by an optical motion capture system and force platform. We calculated timing error based on the difference between the measured impact location (ball position relative to the batter's body at ball-bat impact) and optimal impact location. The timing error between n-th pitch type, (n-1)-th pitch, and the presence or absence of advance information about pitch type (open vs random condition) were analyzed using three-way repeated ANOVA. The results showed that the (n-1)-th pitch type did not affect the timing of impact (p = 0.338). In contrast, the timing errors in open conditions were fewer compared to random conditions (p < 0.001). These results indicate that the pitch type sequence has insignificant effects, and advance information about pitches affects the timing errors. Therefore, having two or more pitch types, reducing the fluctuation of the pitching motion, and the early trajectory of the ball between different pitches potentially lead to increase timing errors.

SUBMITTER: Kidokoro S

PROVIDER: S-EPMC7077830 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Does the combination of different pitches and the absence of pitch type information influence timing control during batting in baseball?

Kidokoro Shuji S Matsuzaki Yuji Y Akagi Ryota R

PloS one 20200317 3

Baseball pitchers use various pitch types to reduce hitting accuracy, but little is understood of the practical strategy of using visuomotor skills and timing control to respond to different pitches. This study examined 1) effectiveness of pitch type combinations, and 2) relationship between the presence and absence of advance information about the next pitch and the timing error. Twenty-six high school baseball players hit a ball launched from a pitching machine in a combination of fastballs (3 ...[more]

PMID: 32182276

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Project description:Purpose To evaluate and describe the differences in characteristics between the Major League Baseball (MLB) pitchers with greater workload and career longevity in terms of innings pitched (IP) and performance-matched controls who have not experienced similar length careers. Methods Using publicly available data, we identified the top 100 MLB pitchers in terms of career IP. Controls were matched to the top 100 pitchers by draft year and round. Pitchers with fewer than 400 IP were excluded. Demographic information, performance statistics, and injury history were reviewed. Logistic regression analysis and Mann–Whitney U tests were used to compare data. Results Compared with controls, the top 100 pitchers in terms of IP were drafted at a younger age (19.35 vs 19.83, P < .001) and in later rounds (6.16 vs 2.45, P < .001). They made their MLB debut at a younger age (21.77 vs 23.12, P < .001). They also pitched fewer innings before debut (470.59 vs 632.07, P = .007), were older at their first (30.72 vs 27.50 years, P < .001) and second (32.42 vs 29.43 years, P < .001) designations to the injured list (IL), and had a significantly longer time from debut to first (3063.50 vs 1565.59 days, P < .001) and second (3712.10 vs 2202.03 days, P < .001) IL trips. The top 100 pitchers were 7.45 times less likely to have made a trip to the IL within 8 seasons from their debut and were 4.04 times more likely to be younger than 24 years at their major league debut. Conclusions Pitchers with the greatest number of IP in their MLB careers were significantly younger when drafted and when they made their major league debut, although this age difference is likely clinically insignificant. Pitchers who were drafted or debuted at a later age accumulate more pre-debut innings and this may contribute to fewer total IP in the MLB. Similarly, later trips to the injured list and longer duration from debut to first or second trip to the IL, but not total IL trips, are predictive of longer careers compared to age and draft class matched controls. Level of Evidence III, retrospective cohort study.

Project description:BackgroundPitch count recommendations are used to reduce injury risk in youth baseball pitchers and are based chiefly on expert opinion, with limited scientific support. Furthermore, they only account for pitches thrown against a hitter and do not include the total number of throws on the day a player pitched. Currently, counts are recorded manually.PurposeTo provide a method using a wearable sensor to quantify total throws per game that is compliant with Little League Baseball rules and regulations.Study designDescriptive laboratory study.MethodsEleven male baseball players (age, 10-11 years) from an 11U (players 11 years and younger) competitive travel team were evaluated over a single summer season. An inertial sensor was placed above the midhumerus of the throwing arm and was worn during baseball games across the season. A throw identification algorithm capturing all throws and reporting linear acceleration and peak linear acceleration was used to quantify throwing intensity. Pitching charts were collected and used to verify actual pitches thrown against a hitter in a game versus all other throws identified.ResultsA total of 2748 pitches and 13,429 throws were captured. On the day a player pitched, he averaged 36 ± 18 pitches (23%) and 158 ± 106 total throws (pitches in game as well as all warm-up pitches and other throws during game). In comparison, on a day a player did not pitch, he averaged 119 ± 102 throws. Across all pitchers, 32% of all throws were low intensity, 54% were medium intensity, and 15% were high intensity. The player with one of the highest percentages of high-intensity throws did not pitch as their primary position, while the 2 players who pitched most often had the lowest percentages.ConclusionTotal throw count can be successfully quantified using a single inertial sensor. Total throws tended to be higher on days a player pitched compared with regular game days without pitching.Clinical relevanceThis study provides a fast, feasible, and reliable method to obtain pitch and throw counts so that more rigorous research on contributing factors to arm injury in the youth athlete can be achieved.

Dataset Information

Does the combination of different pitches and the absence of pitch type information influence timing control during batting in baseball?

Publications

Does the combination of different pitches and the absence of pitch type information influence timing control during batting in baseball?

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