Innovation and Technology in Sports by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9789819902972
Publisher: Springer Nature Singapore

5 Conclusion

This study research investigates whether goal orientation impacts player performance and has been clarified using machine learning of artificial neural network as a result of confirmation. 32 parameters have been tested for 223 athletes using PCA and have been minimised to only 21 parameters from performance parameters. Using HACA, 3 clusters, HTHE, LTME, and MTLE, have been identified that different the athletes by task and ego parameters. Next, using DA to combine cluster and performance parameters that contribute to athlete’s results achievements by using DA research get to narrow down the performance that contributes the biggest to the study and combine the goal orientation from athletes. Lastly, using machine learning to identify the parameter that contributes the most to athletes shows that from 32 to only 13 parameters, including task and ego orientation. Show that only 13 parameters contribute to athletes’ performance with goal orientation of athletes.

Summarize it, showing that results from HTHE and 13 parameters need to sharpen so that athletes can perform much better and even more incredible, resulting in an athlete with better achievement not just in psychology but also in their performance. It can help the player to have a better future in order to become a professional player in future.

References

1.

Reilly T, Williams AM, Nevill A, Franks A (2000) A multidisciplinary approach to talent identification in soccer. J Sports Sci 18(9):695–702

Download

Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.