Effort-dependent effects on uniform and diverse muscle activity features in skilled pitching.

How do skilled players change their motion patterns depending on motion effort? Pitchers commonly accelerate wrist and elbow joint rotations via proximal joint motions. Contrastingly, they show individually different pitching motions, such as in wind-up or follow-through. Despite the generality of the uniform and diverse features, effort-dependent effects on these features are unclear. Here, we reveal the effort dependence based on muscle activity data in natural three-dimensional pitching performed by skilled players. We extract motor modules and their effort dependence from the muscle activity data via tensor decomposition. Then, we reveal the unknown relations among motor modules, common features, unique features, and effort dependence. The current study clarifies that common features are obvious in distinguishing between low and high effort and that unique features are evident in differentiating high and highest efforts.

Influence of Release Parameters on Pitch Location in Skilled Baseball Pitching.

This study explored the mechanical factors that determine accuracy of a baseball pitching. In particular, we focused on the mechanical parameters at ball release, referred to as release parameters. The aim was to understand which parameter has the most deterministic influence on pitch location by measuring the release parameters during actual pitching and developing a simulation that predicts the pitch location from given release parameters. By comparing the fluctuation of the simulated pitch location when varying each release parameter, it was found that the elevation pitching angle and speed significantly influenced the vertical pitch location, and the azimuth pitching angle significantly influenced the horizontal pitch location. Moreover, a regression model was obtained to predict the pitch location, and it became clear that the significant predictors for the vertical pitch location were the elevation pitching angle, the speed, and spin axis, and those for the horizontal pitch location were the azimuth pitching angle, the spin axis, and horizontal release point. Therefore, it was suggested that the parameter most affecting pitch location weas pitching angle. On the other hand, multiple regression analyses revealed that the relation between release parameters varied between pitchers. The result is expected to contribute to an understanding of the mechanisms underlying accurate ball control skill in baseball pitching.

Cross-sectional comparison of the probabilistic structure in the distribution of pitching location among baseball pitchers of different ages.

The present study was a cross-sectional comparison of probabilistic structure in the distribution of pitching location among baseball pitchers of various age groups (25 elementary school (ES), 20 junior high school (JH), 15 high school (HS), and 18 college students (CL)). In the results, despite the general age-dependent variations in pitching precision, the difference was reflected not only in error 'size' but also in the 'shape' of error as it was shown by fitting 95% confidence ellipse to the two dimensional distribution of pitch location. While the precision measure as a reflection of trial-by-trial variability of release timing (major axis length of the ellipse) was constant, minor axis length of the ellipse as a reflection of variability in the pitching form of each participant demonstrated significant differences among the groups. In the ES group particularly, the trial-by-trial variability in the trajectory angle of the throwing arm was significantly correlated with the minor axis length; this correlation was far greater than those in older groups. The present study is the first to demonstrate the detailed structure of the variability of pitching location of baseball dependent on age.

Baseball pitching accuracy: an examination of various parameters when evaluating pitch locations.

This study evaluated baseball pitching accuracy using a variety of parameters to quantify pitching errors and analysed the validity of the accuracy measurements by comparing the outcomes of two small groups of pitchers. Several professional (n = 5) and high school (n = 8) pitchers threw 30 pitches each, including 20 fastballs and 10 breaking balls. To assess pitching accuracy, pitch locations relative to the catcher's mitt (as the target) were evaluated with various parameters, including major/minor radius, an area of 95% confidence ellipse, absolute error, constant error and pitch location trajectory. Compared to the high school pitchers, the professional pitchers exhibited shorter major and minor radii in their 20 fastball pitches (p < 0.05), more accurate control in the lateral direction (p < 0.05), and shorter pitch location trajectories (p < 0.05). The evaluation methods presented in this study can objectively assess pitching accuracy and may thus provide useful coaching feedback with visual information.

A Preseason Checklist for Predicting Elbow Injury in Little League Baseball Players.

BACKGROUND: Despite pitch count limits, the incidence of Little League elbow is increasing. A risk-evaluation tool capable of predicting which players are predisposed to throwing injury could potentially prevent injuries. PURPOSE: To investigate the effectiveness of a risk factor checklist for predicting elbow injury in Little League baseball players during 1 season. The hypothesis was that a preseason risk-evaluation checklist could predict which players were predisposed to elbow injury. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: A preseason risk-evaluation checklist was distributed to Little League baseball teams in Japan. Six months later, a follow-up questionnaire was mailed to determine injuries sustained during the season. Logistic regression analysis was performed, assigning presence or absence of elbow injury during the season as the dependent variable, and an injury risk score (IRS) was developed based on the statistically significant variables. Receiver operating characteristic (ROC) curve analysis was conducted to determine the predictive validity of the checklist and the optimal cutoff IRS. RESULTS: Data from 389 Little League players were analyzed. Among them, 53 players experienced an elbow injury requiring medical treatment during the season. Six checklist items associated with a medical history of throwing injury, pitch volume, and arm fatigue were found to be significant. Responses to the items could predict the players who were susceptible to injury during the season, with a two-thirds cutoff value for a 6-item checklist (area under the curve, 0.810; sensitivity, 0.717; specificity, 0.771). CONCLUSION: Results from a 6-item preseason checklist can predict which Little League players are to sustain an elbow injury by the end of the season. CLINICAL RELEVANCE: The ability to predict which Little League baseball players are predisposed to elbow injury allows parents and coaches to initiate preventive measures in those players prior to and during the baseball season, which could lead to fewer elbow injuries.