Analysis of Softball Performance of the Players in Relation to their Anthropometric Profile

Jadhav Jayant Bhalchandra1*, Dr. Atul Shukla2

1 Research Scholar, Kalinga University, Raipur (CG), India

2 PhD Guide, Dept. of Physical Education, Kalinga University, Raipur (CG), India

Email - vimtpune@gmail.com

Abstract - Improving one's anticipating and decision-making skills might help one play better in team and fast-ball sports (including tennis, soccer, and softball). One of the traits of expert decision-makers is the ability to recognize increasingly complex signals and draw meaning from those cues. The present investigation is an empirical examination of the correlation between a variety of anthropometric measurements and the efficiency of male softball players. Softball is a worldwide phenomenon, with fans and players all over the world. There hasn't been a lot of study done in the field of softball to delve into the many factors that continue to contribute to success. There is a paucity of published resources pertaining to softball, despite the fact that the sport requires extensive research and analysis in a variety of areas. The study's overarching goal is to analyze the relationships between softball players' anthropometric profiles and physiological characteristics and their pitching performances. Nutritional status may be assessed by looking at patients' skeletons (anthropometry).

Keywords: Softball, Anthropometry, Player, Physical

INTRODUCTION

Video-based perceptual training might be used to assist players get ready for competition, recover from injury, or get through days when field training is not possible due to rain, while being underutilized in the high-performance sporting setting. To improve their offensive and defensive play, athletes may benefit from video-based perceptual training, which helps them see patterns in the action just before a decision is made. These drills may be practiced either defensively or offensively. In spite of the many laboratory evaluations of anticipatory skills, few research have looked at whether or not these gains in ability really transfer to enhanced performance under the pressures of a game-specific situation. A transfer measure is required to determine whether the advantages shown in the lab can be expected to be replicated in the game setting. In addition, a retention test to determine whether or not the improvement in anticipatory ability can be maintained after the training stimulus has been removed is seldom performed in research.

As a result of their widespread adoption, games and sports were an integral part of ancient Greek culture, which is sometimes referred to as the "Golden Age" of this sector of human endeavor. Anthropometry refers to the practice of quantitatively assessing human morphology by calculating averages and variations in length, width, and height. Body measurements include things like weight, height, circumference, skin fold thickness, and skeletal widths and lengths. Anthropometry is a branch of science concerned with the measurement and comparison of human anatomy, physiology, structure, and function. Measuring the human body in terms of skeletal, muscular, and adipose tissue is the subject of this branch of science. Anthropometry has allowed for the evaluation of both form and function at the structural level. The success of an athlete depends on a wide variety of factors. It is generally accepted that the size, shape, and form of one's body, along with other aspects of its physical make-up, have a significant role in this. Athletes are now selected for their physical structure and general body size to compete at a high level in any sport. Physical fitness is defined as the state of being able to do the activities of everyday living without being too tired or exhausted, as well as having the strength and stamina to effectively meet any unforeseen demands that may be placed upon one. For optimal performance, softball players need to be in peak physical condition.

LITERATURE REVIEW

Komínková, Linda & Peric, Tomas (2020) In order to reach the level of mastery required for a certain sport, one might choose one of two routes. Early sport sampling describes the first stage, while early sport specialization describes the second. The 10,000-hour rule and the principle of intentional practise have led researchers to conclude that an early specialization approach to sports training is important to obtain elite athletic performance. An early specialized approach to sports training is thought to be important to acquire top athletic performance, while being linked to poor physical, psychological, and social development implications. Yet, experts who advocate for early sampling point out that athletes might gain from a transfer of talents across sports if they try out a range of activities in childhood before beginning to specialize in their training as adults. They see this as crucial to setting themselves up for future success as they pursue specialized careers. Understanding how early specialization in a sport and the sampling approach to learning a variety of sports contribute to skill acquisition is the primary goal of this research. Conclusions suggest that it is not completely clear which technique is the most effective way to develop competence in a sport, despite the relatively high number of research undertaken in this sector. Contradictory results were found by researchers who looked at the validity of the 10,000-hour rule and the idea of purposeful practice in different sports. Also, studies addressing the early sampling strategy mostly focused on team sports and were conducted using a retrospective design, which indicates that players did not have to recollect their experiences or that the athletes' memory of events may be biased. Research in this area focused on team-based activities. On top of that, the study virtually ever mentions how early the athletes specialized. This is why long-term research are necessary to settle the debate over which approach is best for developing athletic prowess.

Anwar, Choiroel & Budiono, Irwan & Pamot, Hermawan (2019) If children played more traditional games at school, maybe the rising rate of childhood obesity might be slowed. The game will require some tweaks and maybe even some standards to be ready for release to the public. The research team hopes to use the findings of this study to refine a proposal for a reimagined softball game and determine whether or not it may help improve elementary school students' fitness and diet. The development research strategy was used to create the new model of the adapted softball game. 27 fifth-graders from an elementary school participated in field trials using a before-and-after design. Z scores for participants' body mass index and fitness levels were compared before and after the intervention to evaluate its efficacy. The results of this research back up the validity and applicability of the modified softball game as a valid model for analyzing physical education programs. Nutritional quality and physical fitness both increased significantly among elementary school students who participated in a program that included an adapted version of the sport of softball. In order to address the problem of obesity in school-aged children, it is recommended that the modified softball game model be implemented on a regular basis in schools and other relevant stakeholder organizations.

Mujika, Iñigo & Halson, Shona & Burke (2018) Sports periodization has traditionally focused on the exercise component of an athlete's preparation, while neglecting to take into account other aspects that may affect an athlete's readiness for peak competition performances. With the help of integrated periodization, which allows for the coordinated integration of various training components that are optimally suited for a certain phase of training, an athlete's program may be integrated. The goal of this piece is to examine the existing data in favor of integrated periodization. This article will explore the concept of periodization in sports preparation, with a particular emphasis on exercise training, recuperation, nutrition, psychological skills, and skill development. Moreover, we factor in the importance of periodizing heat and altitude adaptation, body composition, and physical treatment. Whereas several methods of periodizing exercise training have come under fire as of late, there is evidence to suggest that they may help athletes of a variety of elite individual and team sports—including soccer—improve their performance. When it comes to the latter, periodization (both physical and strategic) may be useful in coping with the rigors of a professional season, including the requisite amount of travel, weariness, and potential injuries. Recovery therapies should be periodized, meaning that they should be either withheld or emphasized, to have an influence on acute and chronic training adaptation and performance. Athletes may benefit from a periodized training and competition schedule that takes into account the timing of food ingestion in relation to physical activity. The periodization of an athlete's efforts to improve their mental skills should be determined by both their individual needs and the needs of the team as a whole. Incorporating skill development into a periodized training program has the potential to greatly improve an athlete's overall performance.

Mandeep Singh (2018) The researchers set out to identify the anthropometric determinants of softball performance and the link between anthropometric characteristics and performance in the sport. The research drew 150 male softball players from different Indian institutions and states. The anthropometric rod was used to measure the players' height and length. Each athlete's weight was meticulously recorded using a portable weighing machine. The athletes' bodily components were measured using steel tape for circumferences and sliding callipers for diameters. In order to measure the skinfold thicknesses, the Harpenden skinfold calliper was used. Softball performance was shown to be 13% explained by lean body mass, 3% by upper arm circumference, and an extra 3% by upper arm length, according to regression studies. The results show that the most important factor influencing softball performance was the player's lean body mass.

Aswathy V (2019) This research set out to examine the relationship between hand grip strength and anthropometric factors of cricket and softball players competing at the intercollegiate level. Thirty female intercollegiate softball and cricket players, ranging in age from eighteen to twenty-five, participated in the research. For this study, researchers used eleven anthropometric factors and two strength-related variables. The data was gathered at the sports science laboratory of Lakshmibai National College of Physical Education using conventional anthropometric equipment that was provided by well-known Indian and foreign businesses. Unlike cricket players, women's collegiate softball players' grip strength was significantly correlated with the majority of their arm dimensions.

ANTHROPOMETRIC VARIABLES

Height Objective:
Body Weight
Arm Length
Chest Girth
Leg Length

ASSESSMENT OF PERFORMANCE OF SOFTBALL PLAYERS

To assess softball players' ability in many facets of the game, the investigator developed a performance rating scale after consulting with persons widely regarded as authority in the sport.

Performance Rating Scale

Through their input, experts in the field helped shape the Rating Scale's development. The following people were consulted for this article: Mr. Gopinath P, Asst. Coach, Sports Authority of India (SAI), Former International Baseball Player, Silver Medalist, and Current Coach of Indian Baseball Team for Women; Mr. Harsha K, Former National Softball Player and International Baseball Player, and Currently Running a Baseball Club in Bengaluru; Mr. Shankar Narayana H N, a Softball Expert; and Dr. Bhaskar H N, a Softball Expert. The Honourable Mr. Gopina Professionals, a guide, and a researcher all had substantial input towards the development of the softball performance rating system. The experts suggested employing a hybrid subjective-objective grading method to assess the softball players' overall performance.

RESEARCH METHODOLOGY

A variety of anthropometric, physical fitness, and psychological characteristics are related to the performance of male softball players, and this is what the present research is looking at. Information on anthropometrics and softball performance, among other things, was needed for the study. Softball is a worldwide phenomenon, with fans and players all over the world. Just a few of studies have looked at the numerous factors that continue to contribute to high performance in softball.

Selection Of Variables

The study's author read a wide range of scholarly works on the subject of anthropometrics analysis, including papers, coaching guides, journals, and books. The investigation also included the researcher talking to experts in the subject. In addition to the aforementioned literature and expert advice, we also considered the aims of the research and the availability of standard tools for collecting measures and recording data when making our anthropometric measurement selections. Based on these results, the researcher provided the following recommendations for softball players, with the assumption that these traits are necessary for optimal success in the sport.

Statistical Procedure

This study aimed to determine whether or not there was a connection between the anthropometric, fitness, and psychological data of male softball players and their on-field performance. Out of the original softball performance results, standard scores were generated. Karl Pearson's product moment co-efficient was used to analyze the correlation between physical attributes and the performance of the VTU men's softball team. Softball performance was predicted using anthropometric measures and stepwise regression models.

DATA ANALYSIS

The Connection Between Different Variables of Anthropometric Measurement and Performance

Table 1 Analyses of the relationships between anthropometric variables and performance using Pearson's product moment

Variable 1	Variable 2	Pearson Correlation	Significance
Height	Performance	.285	.002
Weight	Performance	.412	.001
Arm length	Performance	.206	.024
Chest girth	Performance	.284	.002
Leg length	Performance	.040	.661

REGRESSIONAL ANALYSIS

Table 2 The values of R, R2, and the corrected R2 from a stepwise multiple regression analysis (DV=Performance; IVs =Anthropometric Variables)

Model	Variables Entered	Variables Removed	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	Weight	.	.412a	.170	.163	5.19148

We found that height is a very significant predictor of on-field performance for softball players using hierarchical multiple regressions. The following was determined by using the Independent Variables of height, shoulder breadth, waist circumference, and leg length. Only weight, out of the five anthropometric parameters, was shown to have a statistically significant influence on softball performance. Calculated R2=.163, squared R=.412, and adjusted R2=.163. Meaning that 16.3% of total performance may be attributable to weight. Nevertheless, this sample's results cannot be predicted using the model since other components were omitted.

Table 3 Results of regressional ANOVA

Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	651.695	1	651.695	24.180	.001
	Residual	3180.271	118	26.951
	Total	3831.967	119

A regression ANOVA yielded a significant result of 24.180 at the.001 level of significance. This lends credence to the theory that softball players' weight is the most important anthropometric indicator of performance.

Table 4 T-values, standardised and unstandardized coefficients, and beta-values

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta	t	Sig.
1	(Constant)	60.580	3.068		19.748	.001
1	Weight	.221	.045	.412	4.917	.001

The predictor model has a beta of.412 in the first phase. The t values of 19.748 and 4.917, when comparing the constant and the predicted model, are statistically significant (p.001).

Table 5 Regression Analysis Step-by-Step Exclusion of Variables

Model		Beta In	t	Sig.	Partial Correlation	Collinearity Statistics
Model		Beta In	t	Sig.	Partial Correlation	Tolerance
1	Height	.108b	1.128	.262	.104	.758
	Arm length	.018b	.193	.847	.018	.784
	Chest girth	-.209b	-1.360	.176	-.125	.296
	Leg length	-.029b	-.345	.731	-.032	.972

Measurements of height, arms, chest, and legs were ruled out in the first phase.

CALCULATING THE CORRELATION BETWEEN ANTHROPOMETRIC MEASURES AND PLAYING ABILITIES

Table 6 Iterative Multiple Regression of Anthropometric Factors on Softball Performance

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
5	0.449	0.202	0.185	4.492

Arm strength is shown to have a substantial influence on softball players' performance in Table 6 among the anthropometric parameters. The computed 'R' value of 0.449 exceeds the minimal 'R' value of 0.2. The 'R' square value shows that the players' arm length contributes for 20% of their total softball performance.

Table 7 Players' Variables in a Softball Equation

Variables	B	SE B	Beta	‘t’	Level of Sig.
(Constant)	42.254	10.435		4.049	0.000
Arm Length	0.482	0.138	0.450	3.487	0.001

Multiple Regression Equation

Softball player batting average on anthropometric variables = 42.254 +0.482 (Arm Length)

Table 8 lists the independent variables (those that were left out of the original equation).

Table 8 Differences in Anthropometric Traits As it does not factor into the equation of top softball players,

Variables	Beta in	‘t’	Significance
Height	-0.018	-0.070	0.944
Weight	0.179	0.847	0.401
Leg Length	0.016	0.061	0.952
Trunk Length	-0.361	-1.563	0.125

The variables that were omitted from the model because their significance was deemed to be less than the 0.05 criterion are shown in table 8. hence, the anthropometric characteristics such as height, weight, leg length, and trunk length are disregarded.

CONCLUSION

Anthropometric factors are crucial to the overall effectiveness of a softball team. The success of a softball team depends on many factors, including the players' individual skills (such as hitting, fielding, throwing, running bases, and catching), the players' interaction with one another in tactical movements, and the players' in-depth familiarity with the position-specific skills necessary for success. Finding talented softball players may benefit from the creation of statistical models that can predict their future performance based on testing conducted in a lab or on a playing field. As such, this study's goal is to determine whether or not anthropometric factors have a role in the athletic performance of female softball players. The purpose of this research was to (1) identify factors that predict softball players' performance, (2) evaluate appropriate data that helps softball players increase relative performance factors to their playing ability, and (3) quantify the performance level of the softball player with respect to the selected variables as anthropometric.

REFERENCE

Komínková, Linda & Peric, Tomas. (2020). The Issue Of Sport Specialization And The Development Of Sport Expertise. Studia sportiva. 13. 84. 10.5817/StS2019-2-8.
Anwar, Choiroel & Budiono, Irwan & Pamot, Hermawan. (2019). Traditional Softball Games Effective Modified for Improving Nutritional Status and Physical Fitness in Elementary School Children. Jurnal Kesehatan Masyarakat. 15. 206-212. 10.15294/kemas. v15i2.21524.
Mujika, Iñigo & Halson, Shona & Burke, Louise & Balague, Gloria & Farrow, Damian. (2018). An Integrated, Multifactorial Approach to Periodization for Optimal Performance in Individual and Team Sports. International Journal of Sports Physiology and Performance. 13. 538-561. 10.1123/ijspp.2018-0093.
Liechty, Toni & West, Stephanie & Naar, Jill & Son, Julie. (2016). Perceptions of ageing among older women softball players. Annals of Leisure Research. 20. 1-19. 10.1080/11745398.2016.1220321.
Paul, Darren & Gabbett, Tim & Nassis, George. (2016). Agility in Team Sports: Testing, Training and Factors Affecting Performance. Sports Medicine. 46. 10.1007/s40279-015-0428-2.
Pradhan, Krishnendu. (2016). Motor Fitness Attributes of Inter University Level Male Soccer and Volleyball Players: A Comparative Study. ACTIVE LIFESTYLE A Complete Journal of Health, Physical Education. 2. 34-39.
Varnell, Michelle & Keenan, Karen & Rafferty, Deirdre & Csonka, Jennifer & Salesi, Karl & Sell, Timothy. (2016). Musculoskeletal Characteristics of the Dominant Shoulder Complex in Intercollegiate Baseball and Softball Players by Position and Sport. Athletic Training & Sports Health Care. 8. 70-81. 10.3928/19425864-20160204-04.
Nachtigal, Jon & Kim, Minhyun & Lee, Kyongmin & Seidler, Todd & Stocz, Mike. (2016). Softball: Nothing Soft about It. Journal of Physical Education, Recreation & Dance. 87. 36-41. 10.1080/07303084.2016.1226220.
Wentzel, Melissa & Travill, Andre. (2015). Relationship among fitness, morphological characteristics, skills and performance in men’s fastpitch softball. South African Journal for Research in Sport, Physical Education and Recreation. 37. 175-186.
Gordon, Barrie. (2015). Developing Thinking Players; Baseball/softball edition.
Sintara, Kawiya & Sonchan, Nikorn. (2015). Physical Fitness of Collegiate Softball Players, Burapha University, Thailand.
Bhagat, Upma & Singh, Amarpreet & Nishan, Singh & Deol, (2015). Comparative Study of Selected Anthropometric, Physical Fitness and Psychological Variables Between Softball and Cricket State Level Boys Players. Indian Journal of Applied Research. 5. 257-260.
Chang, Yu-Kai & Ho, Li-An & Lu, Frank & Ou, Ching-Chieh & Song, Tai-Feng & Gill, Diane. (2014). Self-talk and softball performance: The role of self-talk nature, motor task characteristics, and self-efficacy in novice softball players. Psychology of Sport and Exercise. 15. 139–145. 10.1016/j.psychsport.2013.10.004
Mandeep Singh, (2018) Association of Anthropometric Characteristics and Body Composition with The Performance Among Male Softball Players, European Journal of Physical Education and Sport Science, Vol 11, No 4
Aswathy V, (2019) The relation between hand grip strength with hand anthropometric variable in Inter-University level softball and cricket players, International Journal of Physiology, Nutrition and Physical Education; 4(1): 1901-1904