Most of the approaches made in sports science, particularly in relation to baseball, have been limited to biomechanics studies, such as image analyses of pitching and batting actions (8-10). On the other hand, there have been several studies on anthropometric and physiological characteristics of baseball players (2,4,5,13,18). Nakayama (18) reported on the changes in the physiques of Japanese professional baseball players between 1950 and 2002. For physiological characteristics, Coleman et al. (4) surveyed the running speed and body compositions of 210 professional baseball players from the Houston Astros. Studies have been conducted on the physiological characteristics of Major League Baseball players; Ebben et al. (6) studied the physiological tests adopted by coaches of Major League Baseball teams on strength and physical conditioning and those elements that are considered important to baseball players. In view of the effects of these studies as well as what is practiced in training athletes, physical tests are being utilized more frequently to discover athletic talent, to select players, to plan and determine the effects of muscle training, and to prevent sports-related injuries. However, there have been no detailed studies on the relationship between physical fitness and performance in baseball, the information that trainers on the scene need most urgently.
In investigating the relationship between the outcome of physical tests and the performance of athletes, comparative studies are often conducted among players belonging to the leagues of different skill levels or among regular and nonregular players (11,16,25). In such athletic activities in which performance can be expressed by tangible figures, such as time and distance, it is possible to conduct a detailed study on the relationship between the outcome of physical tests and performance (1,21). Furthermore, there are studies in which multiple regression analysis was employed to predict performance from the data obtained from physical tests (14,19,20,22,24). Like other ball games, it is very difficult to express performance in baseball in figures. However, if one succeeds in elucidating a correlation between the results of physical tests and performance, the trainers on the scene should be able to use the physical tests more effectively. In considering the application of physical tests to actual training, procedures such as field tests that can be easily conducted would be much more valuable than laboratory tests that would require the use of expensive equipment, professional knowledge, and many hours for analyses. The authors have already reported on the relationship between the baseball performance evaluation by coaches and the results of field tests for physical fitness (15). Then 6 test items that were particularly closely related to the results of the performance evaluation were selected from 16 items. Moreover, the results of each physical test and evaluations of performance made simple correlation, partial correlation, and multiple correlation analyses possible. It would be meaningful to conduct a study on subjects of the same age and skill levels to see if the results are similar to those obtained in the authors' previous study. Furthermore, the outcome would reinforce the validity of the physical tests that can be used effectively on the actual scene of training.
In this study, the relationship between the physical fitness of college baseball players found from 6 field tests and a performance evaluation by coaches was investigated. The purpose was to ascertain whether the results are similar to those obtained in the authors' previous study (15). First, the performance evaluated by the coaches was expressed numerically. Then, the test results were compared between the groups of players with high performance ratings and the other group made up of those with low ratings. The relationship between the performance evaluation and the test results was examined in detail. In addition, the changes in the test results educed by specialized practice and training in baseball lasting for 3 years were examined.
Experimental Approach to the Problem
An analysis of performance in ball games is a necessary approach in research if one considers the application of the results to the actual scene of training. For a numerical expression of performances in ball games, the results from official games by individuals and teams may be utilized. However, unless the subjects are professional players who participate in many games throughout the year, the evaluation of performance from the scores or obtaining a sufficient number of subjects is difficult. In the current study, an original method was employed in which the evaluations by some coaches are expressed in T scores. A number of problems are associated with this method, but the results obtained through this are new and may be the information that is most needed on the actual scene of training. The field tests of physical fitness that were used here were selected carefully based on the results of a prior study. These tests were used so that they can be applied to the actual scene of training.
The field tests of physical fitness were conducted on 43 fielders (mean age, 20.7 ± 1.4 years; mean athletic career, 10.9 ± 2.6 years) who belonged to a team from Tohoto University Baseball League Division III. Among these 43, there were 7 catchers, 23 infielders, and 13 outfielders. The tests were conducted with the consent of the test subjects and the team coaches. All subjects signed informed consent documents. The study was approved by the Ethics Committee of Juntendo University Graduate School, Sports and Health Science Research Section. The basic anthropometric characteristics of the subjects were 171.3 ± 4.7 cm for height and 67.9 ± 5.7 kg for weight. Eleven of these subjects were available for a comparable evaluation with the data obtained in the previous study on college freshmen. The changes in the test results after 3 years of baseball training were analyzed. The other subjects and the coaches differed from those of the previous study, but they belonged to a team of the same university.
The subjects were grouped by several methods. From the viewpoint of batting, fielding and running, 3 coaches rated all the subjects on a 7-level scale. After the evaluation values obtained the T scores, the means of the ratings by 3 coaches were computed. For each subject, scores for batting, fielding, and running were obtained. Subjects were stratified into 3 groups (i.e., high group, >0.5 SD; middle group, ±0.5 SD; and low group, <0.5 SD) by each 3 scores. In addition, the subjects were grouped by whether they sat on the bench and those who did not at the fall league match (i.e., regular match).
The field tests of physical fitness were conducted during the official league matches for a fall season. Subjects were in condition to take part in the official league matches but not in condition for training season. The test items were those 6 that showed correlation with the batting, fielding, and running evaluations in the prior study: throwing distance, medicine ball throwing, standing long jump, back strength, T-test, and base running. A 1500-m run had also been found to be related to the fielding evaluation, but because the test involves a certain danger, the official tournament was in progress, and the coaches regarded cardiovascular endurance as a physical element of less importance (6,15), it was not included.
For base running, the time that it took each subject to run from home plate and reach first base was measured in seconds. Two testers measured the time by using a stopwatch, and the mean was recorded. For throwing distance, each subject ran to the baseline at which point he threw the ball; the distance between the baseline and where the ball hit the ground was measured in meters. For medicine ball throwing, a medicine ball weighing 4 kg was used. Each subject stood at the baseline with his back facing where the ball was to be thrown, and he threw the ball over his head. The distance between the baseline and where the ball hit the ground was measured in meters. For the standing long jump, each subject stood with his feet slightly apart and his toes against the baseline and jumped forward with both feet. The length of a straight line that connected the points where the subject's body touched the ground (i.e., the point closest to the baseline) and the center of his 2 feet before the jump was measured in centimeters. For back strength, each subject grasped the handle as he would normally do, with his knees extended. He leaned forward at an angle of 30° while keeping his back straight. Then, he pulled the handle with force by raising his upper body. To determine the strength, a back strength meter (TKK 5102; Takei Scientific Instruments Co., Niigata, Japan) was used. To conduct the T-test, 9-m long lines were drawn in a T shape, and 3 cones were placed with 4.5 m between them on the horizontal part of the T. Each subject stood at the end of the vertical line, dashed forward to touch the center cone, and took sidesteps to the cone at the left end. After touching this cone, he sidestepped to the cone at the right end, and after touching this cone, he returned to the center cone. After touching the center cone, he ran back to the goal. The time from the start to reaching the goal was measured in seconds. This test shows one's agility. All tests were repeated twice, and the better score was used for analysis.
The following analysis was conducted for each test result. Intergroup comparisons were made for each evaluation among the high, middle, and low groups and the groups that did and did not sit on the bench. For the 11 subjects who provided data during the first and fourth years at the university, the changes in the results of the tests on physical fitness were also analyzed. Correlation and partial correlation analyses were conducted on the results of performance evaluation and each test result. The following were combined and analyzed to find multiple correlation coefficients: batting evaluation and back strength; fielding evaluation and throwing distance, medicine ball throwing, standing long jump, and T-test; and running evaluation and base running and medicine ball throwing. Furthermore, each test result was substituted in the multiple regression models to predict the evaluation value and the correlation with the current performance evaluation was examined. The multiple regression models in the earlier study (15) are shown below. The multiple regression model for the evaluation of fielding was the result of a recalculation that excluded the 1500-m run.
For each result of the field test for physical fitness, a mean and SD were computed. To test the differences in the means for 3 different groups, a 1-way analysis of variance was conducted, which was followed by a Scheffe post hoc test. To compare 2 groups, a t-test was conducted. The pairwise t-test was used for a comparison of the results recorded for the 11 subjects in the first and fourth years of college. Intraclass correlation coefficients between the first and second measurements were calculated to evaluate the retest reliability. The significance level was set at 5%.
The distribution of the evaluation values in T scores for batting, fielding, and running is shown in Figure 1 to confirm the pattern of distribution of the coaches' evaluation. The correlation coefficients for the evaluations by 3 coaches are displayed in Table 1. It is shown that in batting, fielding, and running, the evaluation values by these 3 coaches were correlated with a significance level of 1% (Table 1). Test reliability (i.e., intraclass correlation coefficients) between the first and second measurements were calculated as follows: throwing distance, 0.78; medicine ball throwing, 0.84; standing long jump, 0.93; back strength, 0.84; T-test, 0.88; and base running, 0.89.
Each category of evaluation (i.e., batting, fielding, and running) was stratified into 3 groups (i.e., high, middle, and low), and the test results were compared (Table 2). The group rated high for batting was significantly better than the group rated low in medicine ball throwing (p < 0.01), standing long jump (p <0.05), T-test (p < 0.05), and base running (p < 0.05). The group evaluated middle for batting was also significantly better in throwing distance (p < 0.05), standing long jump (p < 0.01), T-test (p < 0.05), and base running (p < 0.01) than the group evaluated low. The group rated high in fielding was significantly better than the group rated low in throwing distance (p < 0.01) and T-test (p <0.05). The group evaluated middle for fielding was significantly better in throwing distance (p <0.05) than the group evaluated low. The group evaluated high for running was significantly better for throwing distance (p < 0.05), medicine ball throwing (p < 0.01), standing long jump (p < 0.01), T-test (p < 0.01), and base running (p < 0.01) than the group evaluated low. In addition, this group was significantly better in T-test (p <0.05) than the middle group. The group evaluated middle for running was significantly better in standing long jump (p < 0.05), T-test (p < 0.01) and base running (p < 0.01) than the group evaluated low. The players who sat on the bench were significantly better in medicine ball throwing (p < 0.05), standing long jump (p < 0.05), T-test (p < 0.01), and base running (p < 0.05) than those players who did not sit on the bench.
When the results of the physical fitness test conducted in 2003 (i.e., the first year of college) were compared against those of 2006 (i.e., the fourth year), significant improvement (p < 0.01) was noted in throwing distance and base running (Table 3).
The multiple correlation coefficients for the combined test items selected in the prior study and the results of the performance evaluation are shown in Table 4. The correlation coefficients between the predicted evaluation values, obtained by substituting the current results into the multiple regression model in the prior study, and the results of evaluation by the coaches are shown in Figure 2. Furthermore, the simple and partial correlation coefficients between the results of the evaluation and test are shown in Table 5. When the effects of fielding and running were removed, the batting evaluation showed a significant correlation with back strength and medicine ball throwing (p < 0.01). Without the effects of batting and running, the evaluation of fielding showed a significant correlation with throwing distance (p < 0.05). With the effects of batting and fielding removed, the running evaluation was significantly related to medicine ball throwing (p < 0.01), standing long jump (p < 0.05), T-test (p < 0.01), and base running (p < 0.01).
First, the distribution pattern of the evaluation by coaches was confirmed. A certain scattering of the evaluation values had been expected. The evaluation by 3 coaches showed medium to high levels of correlation. The evaluation value for each category (i.e., batting, running, and fielding) was divided into 3 groups (i.e., high, middle, and low), and their means were compared. The group rated high in fielding produced significantly high test results in throwing distance (p < 0.01) and T-test (p < 0.05) compared with the group rated low. Throwing distance is employed frequently as 1 of the tests for admission to professional baseball teams in Japan. It is believed that ball throwing is a good test of fielding aptitude. However, it is not very closely related to batting or running; it should be used to evaluate fielding capability only. Throwing distance is directly related to ball throwing velocity, and throwing distance is believed to be a good method to determine a subject's shoulder strength without the use of expensive speed guns (26). Agility determined by a T-test represents the element representing physical fitness that baseball coaches believe is essential in baseball players (6,15). In fielding that requires instant responses to balls that come at a player in many ways, agility is considered a valuable asset. As in the previous study (15), those players with a high evaluation for running exhibited significantly higher base running capability than those players who were rated low. The evaluation of running ability appears to include the technique to reach each base smoothly. However, at the college level, it is believed that everyone has already mastered this and the ability to run a standard short distance fast is directly related to the running evaluation. On the other hand, base stealing requires the player to make quick judgments of the situation and at a moment when the pitcher or fielder is off guard. Some elements, such as the ability to steal bases, cannot be measured by physical tests.
The results of this study were not altogether consistent with those of the previous study (15). In the previous study, no significant differences were noted in the test results between the group rated high in batting and the group rated low. A correlation of only 0.4 was noted between back strength and the batting evaluation. In the current study, however, significant differences were noted in several test results for these 2 groups. Furthermore, some test items showed correlation with the batting evaluation. Muscular strength and power probably have an effect on swinging speed or ball hitting velocity, so an evaluation or training of muscle strength is most likely necessary. In fact, the coaches in charge of strengthening and conditioning Major League Baseball players place an emphasis on building muscle strength and muscle power (6). For other factors that may produce these results, a high degree of correlation was found between the evaluation of fielding or running and the batting evaluations. In the current study, those players who were rated high in fielding and running were also rated high for batting, and this finding may explain the result cited above. For example, when the partial correlation between batting evaluation and the test results was examined, a significant correlation was found with back strength and medicine ball throwing. It appears that batting is strongly related to physical elements, such as muscle strength and muscle power.
In comparing the test results of those players who sat on the bench and those who did not, significant differences were noted in several items. On the whole, one may conclude that those players who were given opportunities to participate in official matches generally have better physical fitness than those who were not. However, one should note that among those who sat on the bench, there were substitute hitters, fielders, and runners and others who were selected because of their outstanding performance in 1 category only. Through this kind of grouping of players, comparative evaluations of their performance and results of physical tests are necessarily limited.
For the 11 subjects, it was possible to investigate the changes in the test results brought about by specialized baseball practice and training that lasted for 3 years. Significant improvement was noted in throwing distance and base running. The results represented an improvement in capacity that is unique to baseball. Lately, a number of studies have been conducted on the development of physical or performance tests that are specific to certain types of sports (3,7,12). It is conceivable that those tests specifically designed for a certain type of sport will be more strongly related to performance. For baseball, the tests are not limited to throwing distance and base running; development and utilization of other unique physical tests are awaited. In the current study, only 11 subjects were able to provide all the necessary data. These 11 subjects included the players who sat on the bench 3 years ago, players who exhibited improvement, and those who did not. In the future, it will be necessary to increase the number of subjects so that analyses may be possible by grouping the players according to their characteristics.
In investigating the relationship between the performance and physical tests, if the subjects are professional baseball players who play in more than 100 games each year, official records, such as batting average and the number of home runs, may be used as performance data that are expressed numerically. Other baseball players play in, at most, 10 to 15 games in a short time span per season. Only about 10 regular players are available for the analysis of their data. Regarding the quantification of baseball performance based on the coaches' evaluation as in the current study, there are some questions to be reconsidered, such as the use of coaches of the team, the number of evaluators, and the 7-level evaluation. However, the results of each physical test and evaluations of performance made simple correlation, partial correlation, and multiple correlation analyses possible. The approach taken in this study may offer an advantage as a new research technique or a method to obtain data that are useful on the actual scene of training.
Through a multiple correlation analysis by combining the tests and analysis of the goodness of fit of the multiple regression model, an intermediate or better correlation was found between the physical tests and performance evaluations. These combinations of tests and the multiple regression model were obtained in previous study (15). In addition, the 16 test items were measured. It is readily conceivable that the goodness of fit may vary even in the same team if the subjects or evaluators were different. In some studies in which performance was predicted from the physical test results (14,19,20,22,24), high multiple regression coefficients were obtained, perhaps because in these studies, performance is predicted in sports other than ball games, such as running and rowing. There have not been any reports on surveys on reliability in these multiple regression models. Therefore, results such as those given above were obtained by employing only 6 test items, which is noteworthy. In baseball, a ball game, it is certain that there is a relationship between the performance and the results of field tests. However, it is also true that techniques and other factors in addition to physical fitness have significant effects on the performance of ball games, such as baseball. It has been reported recently that athletic performance is related to visual function (17,23). Surveys on the elements that could not be measured by conventional tests and the development of physical fitness tests specific to baseball performance may be much needed.
From these observations, it has become evident that in the current study, there was a relationship between physical fitness and performance in baseball. It may be said that among college baseball players, batting ability is related to muscle strength and muscle power, fielding ability to throwing capacity and agility, and running ability to agility, power, and running speed. As a source of information in training to improve performance in baseball or as a means to select players, it would be effective to use throwing distance, back strength, medicine ball throwing, standing long jump, T-test, and base running. However, one may predict that the relationship between performance and physical tests may be affected by differences in players, coaches, team policies, and performance levels. Therefore, the evaluation of players should be performed for each team before investigating its relationship with the physical test.
Through advances in sports science, physical tests have come to be utilized for purposes such as finding talented athletes, selecting players, setting goals and evaluating the results of muscle training, and preventing injuries. However, there have been criticisms among trainers (e.g., that the results of physical tests cannot be used effectively). It is not certain which materials should be applied, and there is no adequate budget or equipment to conduct these tests (15). Thus, by conducting a survey, as in the current study, on the test items that are strongly related to athletic performance and that can be readily conducted, physical tests that can be applied effectively to the actual scene of training may be suggested.
The results of this study established that the results of determination of muscle strength and muscle power (e.g., back strength and medicine ball throwing) are related to batting evaluation; the results of testing for throwing capability and agility (e.g., throwing distance and T-test) to fielding evaluation; and the results of the tests for agility, power, and short distance running speed (e.g., T-test, standing long jump, and base running) to running evaluation. Therefore, the belief is that these tests can be effectively applied to actual training programs. However, the test results will be affected by the players, trainers, and level of athletic performance level. To solve such problems, the performance of players should be numerically expressed on each team before investigating its relationship with the test scores. For a simple method of quantification, T-score conversion from evaluation by coaches is recommended. Thus, the test items that are suitable for the policies and style selected for a team are prepared and serve as a source to be used effectively in actual scene of training. It may be necessary to investigate the relationship of performance to the 3 elements that are unique in baseball batting, fielding, and running. It is believed that studies by this approach will yield practical and useful information.
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Keywords:© 2008 National Strength and Conditioning Association
batting; fielding; running; evaluation of baseball performance; multiple regression; partial correlation