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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Predictive Analysis of position specific nutritional requirements in youth players using machine learning and data science techniques |
| Authors Name: | Aditya Nema |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_204787
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| Published Paper Id: | IJNRD2309067 |
| Published In: | Volume 8 Issue 9, September-2023 |
| DOI: | |
| Abstract: | Aspiring young soccer players have a unique set of nutritional requirements owing to the sport being a high energy expenditure nature game as well as accelerated growth of players at this age. Soccer is still an emerging sport in India, and oftentimes those who belong to economically weaker sections of society do not have accessibility to professional guidance for appropriate nutrition management. However, with the improvement in technology, along with increased accessibility and affordability of internet in most parts of the country it is possible to make this nutritional knowledge easily accessible to young players through the internet. Recent advancement in machine learning and data science technology has great potential to bridge this knowledge gap. The purpose of this study is to assess the feasibility of using machine learning and data science techniques in predicting nutritional requirements of young players customized to their playing position and to equip them with information regarding their caloric requirements from each source. The predictive capabilities of machine learning can be further used to empower players by identifying their nutritional deficiencies and recommending supplements or diet plans for their recovery as per their playing positions and metabolic requirements. |
| Keywords: | Soccer, Adolescent players, Machine Learning, Data Science Technology, Nutritional requirements, diet plans, playing position |
| Cite Article: | "Predictive Analysis of position specific nutritional requirements in youth players using machine learning and data science techniques", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 9, page no.a547-a566, September-2023, Available :http://www.ijnrd.org/papers/IJNRD2309067.pdf |
| Downloads: | 000118760 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2309067 Registration ID: 204787 Published In: Volume 8 Issue 9, September-2023 DOI (Digital Object Identifier): Page No: a547-a566 Country: Jabalpur, Madhya Pradesh, India Research Area: Health Science Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2309067 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2309067 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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