This repository contains material supplementary to a paper titled "Effects of individualized training program based on genetic profiling on young soccer players' performance." Each attachment is a crucial element that adds value to the entire project and documentation related to the publication. Familiarizing yourself with the descriptions below will help you understand their purpose, content, and the context in which they were placed.Comparison of results to the previous year of work suplement 6.xlsx - The paper describes the research groups in relation to their work with the same training methodology in the year preceding the study.Detailed description of motor tasks planned in stages 1 and 2 of the experiment suplement 2.pdf.Genetic profiling - Recommendations for individual work suplement 1.pdf - Initial data used at the planning stage.Concept - work (division into subgroups) suplement 3.pdfS&C template .xlsx Action plan and recommendations for implementation for motor preparation coaches and head coaches were implemented in the second stage of testing.The concept of introducing modifications to the classic training microcycle in accordance with genetic indications suplement 5.pdfRAW DATA - RKS Raków Częstochowa.xlsxGenetic Testing Informed Consent Form (blank) EN.docx

This repository contains material supplementary to a paper titled "Effects of individualized training program based on genetic profiling on young soccer players' performance." Each attachment is a crucial element that adds value to the entire project and documentation related to the publication. Familiarizing yourself with the descriptions below will help you understand their purpose, content, and the context in which they were placed.Comparison of results to the previous year of work suplement 6.xlsx - The paper describes the research groups in relation to their work with the same training methodology in the year preceding the study.Detailed description of motor tasks planned in stages 1 and 2 of the experiment suplement 2.pdf.Genetic profiling - Recommendations for individual work suplement 1.pdf - Initial data used at the planning stage.Concept - work (division into subgroups) suplement 3.pdfS&C template .xlsx Action plan and recommendations for implementation for motor preparation coaches and head coaches were implemented in the second stage of testing.The concept of introducing modifications to the classic training microcycle in accordance with genetic indications suplement 5.pdfRAW DATA - RKS Raków Częstochowa.xlsxGenetic Testing Informed Consent Form (blank) EN.docx

This repository contains supporting materials for the article entitled “Winners' strategies: Comprehensive analysis and optimization of 2-point shots in 3x3 basketball using multi-criteria decision support analysis, on the example of two Olympic National Teams", divided into the following parts.A. Code and MCDA analysis :analysis.ipynbcomet_model_improvement_5%.xlsxcomet_model_improvement_10%.xlsxcomet_model_improvement_20%.xlsxcomet_results_[0.3 0.7].xlsxcomet_results_[0.4 0.6].xlsxcomet_results_[0.5 0.5].xlsxcomet_results_[0.6 0.4].xlsxcomet_results_[0.7 0.3].xlsxpreprocessed_decision_matrix.xlsxSRB.xlsxPL.xlsxB. Raw data for analysisOpis.docx - parameter definitionsbaza danych 3x3.xlsx - data summaryC. Sample input data - VideoSerbia - Łotwa.mov - raw video data from the Olympic competition between the Serbian and Latvian teamsPolska - Japonia.mov - raw video data from the Olympic competition between the Poland and Japan teams

This repository contains supporting materials for the article entitled “Winners' strategies: Comprehensive analysis and optimization of 2-point shots in 3x3 basketball using multi-criteria decision support analysis, on the example of two Olympic National Teams", divided into the following parts.A. Code and MCDA analysis :analysis.ipynbcomet_model_improvement_5%.xlsxcomet_model_improvement_10%.xlsxcomet_model_improvement_20%.xlsxcomet_results_[0.3 0.7].xlsxcomet_results_[0.4 0.6].xlsxcomet_results_[0.5 0.5].xlsxcomet_results_[0.6 0.4].xlsxcomet_results_[0.7 0.3].xlsxpreprocessed_decision_matrix.xlsxSRB.xlsxPL.xlsxB. Raw data for analysisOpis.docx - parameter definitionsbaza danych 3x3.xlsx - data summaryC. Sample input data - VideoSerbia - Łotwa.mov - raw video data from the Olympic competition between the Serbian and Latvian teamsPolska - Japonia.mov - raw video data from the Olympic competition between the Poland and Japan teams

This repository contains material auxiliary to paper titled "Forecasting extremes of football players' performance in matches", divided into the following parts.A. Athlete performance parameters, as generated from the Apex Pro Series, STATSports, Premium System6072023, Sonra 4.0"Appendix A.pdf"B. Sample datasets used in modeling"Appendix B.xlsx" - an athelete's performance log as produced by STATSports systemmatch-day-gps.csv - an athlete's GPS trace on a match day (MD)md-5-training-gps.csv - the athlete's GPS trace on a training session 5 days before MDC. Sample models and modeling resultsZ_cnt.py - sample pre-processed and aggregated GPS data, used further in modelingzenodo_gps_demo.py - a scipt examining a range of time vs. speed definitions of an interval that correlate training and match performace bestzenodo_apx_demo.py - a script generating sample models from APX-Data

This repository contains material auxiliary to paper titled "Forecasting extremes of football players' performance in matches", divided into the following parts.A. Athlete performance parameters, as generated from the Apex Pro Series, STATSports, Premium System6072023, Sonra 4.0"Appendix A.pdf"B. Sample datasets used in modeling"Appendix B.xlsx" - an athelete's performance log as produced by STATSports systemmatch-day-gps.csv - an athlete's GPS trace on a match day (MD)md-5-training-gps.csv - the athlete's GPS trace on a training session 5 days before MDC. Sample models and modeling resultsZ_cnt.py - sample pre-processed and aggregated GPS data, used further in modelingzenodo_gps_demo.py - a scipt examining a range of time vs. speed definitions of an interval that correlate training and match performace bestzenodo_apx_demo.py - a script generating sample models from APX-Data