Pitched-baseball trajectories were measured in three dimensions during competitions at the 1996 Summer Olympic games using two high-speed video cameras and standard DLT techniques. A dynamic model of baseball flight including aerodynamic drag and Magnus lift forces was used to simulate trajectories. This simulation together with the measured trajectory position data constituted the components of an estimation scheme to determine 8 of the 9 release conditions (3 components each of velocity, position, and angular velocity) as well as the mean drag coefficient CD and terminal conditions at home plate. The average pitch loses 5% of its initial velocity during flight. The dependence of estimated drag coefficient on Reynolds number hints at the possibility of the drag crisis occurring in pitched baseballs. Such data may be used to quantify a pitcher’s performance (including fastball speed and amount of curve-ball break) and its improvement or degradation over time. It may also be used to understand the effects of release parameters on baseball trajectories.
LeRoy W. Alaways, Sean P. Mish and Mont Hubbard
Jason R. Themanson, Nicole J. Bing, Brad E. Sheese and Matthew B. Pontifex
better understanding of batting at behavioral, cognitive, and neural levels, a great deal remains unexplored. One notable gap in the literature relates to the measurement of dynamic batting perceptual processes during ongoing pitch-by-pitch sequences and the variables that may influence neural indices
Hardeep Singh, Mark Lee, Matthew J. Solomito, Christian Merrill and Carl Nissen
, or soccer. 3 , 4 , 10 – 13 One explanation for the diverse presentation may be that primary lumbar extension exists in a variety of athletic movements but is not recognized, as the necessarily complex spine motion of sport masks lumbar extension. Baseball pitching is an extremely intricate motion
Brett S. Pexa, Eric D. Ryan, Elizabeth E. Hibberd, Elizabeth Teel, Terri Jo Rucinski and Joseph B. Myers
Baseball pitching is a dynamic movement that results in some of the highest kinematic and kinetic values in sport. Pitchers generate glenohumeral internal rotation angular velocities of over 7000° per second and internal rotational torques of 94 to 96 Nm. 1 At ball release, the shoulder moves from
Yungchien Chu, Glenn S. Fleisig, Kathy J. Simpson and James R. Andrews
The purpose of the current study was to identify the biomechanical features of elite female baseball pitching. Kinematics and kinetics of eleven elite female baseball pitchers were reported and compared with eleven elite male pitchers. Results suggested that females share many similarities with males in pitching kinematics, with a few significant differences. Specifically, at the instant of stride foot contact, a female pitcher had a shorter and more open stride and less separation between pelvis orientation and upper torso orientation. From foot contact to ball release, a female pitcher produced lower peak angular velocity for throwing elbow extension and stride knee extension. Ball velocity was lower for the female. Foot contact to ball release took more time for a female pitcher. Maximal proximal forces at the shoulder and elbow joints were less for a female pitcher.
Maurice Vergeer and Leon Mulder
popular there. Why some players are extremely popular while others are less popular is a question that has not yet been addressed by academics: Does online popularity result from players’ performance on the pitch or from the mere fact that they play with a successful team? Or could the key factor be their
Rob Gray, Anders Orn and Tim Woodman
shown a “heat map” representing a particular hitter’s batting average for pitch locations throughout the strike zone. While it has been shown that athletes can use this type of information to improve performance (e.g., Alain & Proteau, 1980 ; Gray, 2015a , 2015b ), it has the potential to change how
Steven W. Barrentine, Tomoyuki Matsuo, Rafael F. Escamilla, Glenn S. Fleisig and James R. Andrews
Previous researchers studying baseball pitching have compared kinematic and kinetic parameters among different types of pitches, focusing on the trunk, shoulder, and elbow. The lack of data on the wrist and forearm limits the understanding of clinicians, coaches, and researchers regarding the mechanics of baseball pitching and the differences among types of pitches. The purpose of this study was to expand existing knowledge of baseball pitching by quantifying and comparing kinematic data of the wrist and forearm for the fastball (FA), curveball (CU) and change-up (CH) pitches. Kinematic and temporal parameters were determined from 8 collegiate pitchers recorded with a four-camera system (200 Hz). Although significant differences were observed for all pitch comparisons, the least number of differences occurred between the FA and CH. During arm cocking, peak wrist extension for the FA and CH pitches was greater than for the CU, while forearm supination was greater for the CU. In contrast to the current study, previous comparisons of kinematic data for trunk, shoulder, and elbow revealed similarities between the FA and CU pitches and differences between the FA and CH pitches. Kinematic differences among pitches depend on the segment of the body studied.
Adam Culiver, J. Craig Garrison, Kalyssa M. Creed, John E. Conway, Shiho Goto and Sherry Werner
Pitching is a series of dynamic movements that require full body coordination and utilization of the entire kinetic chain. The pitching motion consists of 6 phases: windup, stride, arm cocking, arm acceleration, arm deceleration, and follow-through. 1 Pitchers generate energy in the windup, stride
Norihisa Fujii and Mont Hubbard
A simulation and optimization procedure was constructed to investigate the relationships between optimal movement and muscular strength for baseball pitching. Four segments (torso, upper arms, lower arms, hands) and six torque generators (shoulders, elbows, wrists) are modeled. The torque generators have torque-angle and torque-angular velocity characteristics of Hill-type muscle function. The optimization objective function includes release velocity and negative terms penalizing joint loading and inaccuracy. The weighting coefficient for joint loads has a strong influence on the results. As this coefficient increases, the motion becomes more similar to actual measured pitches. Combining active state patterns optimized for different weighting coefficients gives larger joint loads in the simulated motion. This supports the hypothesis that well-coordinated active states are important for controlling the relationships of the different torque generators in order to create a reasonable and effective pitching motion. The model proposed here is superior to previous simulations for throwing, from the viewpoint of modeling with characteristics of Hill-type muscle function, and can be used to explore realistic baseball pitching.