Multi-criteria assessment and ranking system of sport team formation based on objective-measured values of criteria set

Abstract Basketball is one of the most popular sports games in the world. Professional basketball has become a significant contributor to global economics and business. Considerable funds attracted by the game motivate participants of the sporting process (players, coaches, club owners, administration and etc.) to strive for better athletic results, this way promoting internal and external rivalry. A large number of players and the desire of teams to attract better team members as well as improve the quality of the already available athletes, boost the use of assessment and rating processes. The most popular and widely used player rating systems are based on performance statistics, which reflect situational factors of the game. Most specialists believe that such systems lack objectivity. Meanwhile, the Authors suggest a systematic solution, i.e. an adjusted well-known TOPSIS method and principles for the design of the algorithm based on the method. As a consistent problem solving system, algorithms based on multi-criteria decision-making are regarded to be simple and clear, suitable to substantiate solutions as well as easily applied in practise. Methodologies used by the Authors will help ensuring a greater efficiency of player and team rating, more accurate prognoses of sports results, team formation, and optimisation of the training process considering individualism of team players and encouraging their versatility, i.e. conformity to general physical preparedness norms of the team. The suggested research methods could be used in other sports. Furthermore, these principles could be used in business management for team formation.

[1]  Ravi Shankar,et al.  An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India , 2012 .

[2]  Madjid Tavana,et al.  A fuzzy inference system with application to player selection and team formation in multi-player sports , 2013 .

[3]  Edmundas Kazimieras Zavadskas,et al.  Integrated multi-criteria decision making model based on wisdom-of-crowds principle for selection of the group of elite security guards , 2013 .

[4]  Mostafa Jafari,et al.  Evaluation model of business intelligence for enterprise systems using fuzzy TOPSIS , 2012, Expert Syst. Appl..

[5]  Abdollah Hadi-Vencheh,et al.  A new fuzzy TOPSIS method based on left and right scores: An application for determining an industrial zone for dairy products factory , 2012, Appl. Soft Comput..

[6]  María Teresa Lamata,et al.  The LTOPSIS: An alternative to TOPSIS decision-making approach for linguistic variables , 2012, Expert Syst. Appl..

[7]  Leonas Ustinovichius,et al.  Attributes Weights Determining Peculiarities in Multiple Attribute Decision Making Methods , 2010 .

[8]  Rodolfo Lourenzutti,et al.  The Hellinger distance in Multicriteria Decision Making: An illustration to the TOPSIS and TODIM methods , 2014, Expert Syst. Appl..

[9]  Andrés José Picazo Tadeo,et al.  Can we be satisfied with our football team? Evidence from spanish professional football , 2008 .

[10]  J. M. Bevan,et al.  Rank Correlation Methods , 1949 .

[11]  R Margaria,et al.  Measurement of muscular power (anaerobic) in man. , 1966, Journal of applied physiology.

[12]  J E Cotes,et al.  Lung volumes and forced ventilatory flows , 1993, European Respiratory Journal.

[13]  Zheng-Xin Wang,et al.  Evaluation of the provincial competitiveness of the Chinese high-tech industry using an improved TOPSIS method , 2014, Expert Syst. Appl..

[14]  Davide Aloini,et al.  A peer IF-TOPSIS based decision support system for packaging machine selection , 2014, Expert Syst. Appl..

[15]  Jack K. Nelson,et al.  Practical measurements for evaluation in physical education , 1974 .

[16]  B. C. V. Zomeren,et al.  REPORT WORKING PARTY: STANDARDIZATION OF LUNG FUNCTION TESTS , 1983 .

[17]  S. Ostojić,et al.  PROFILING IN BASKETBALL: PHYSICAL AND PHYSIOLOGICAL CHARACTERISTICS OF ELITE PLAYERS , 2006, Journal of strength and conditioning research.

[18]  Gwo-Hshiung Tzeng,et al.  Comments on “Multiple criteria decision making (MCDM) methods in economics: an overview” , 2012 .

[19]  Michael Vitale,et al.  The Wisdom of Crowds , 2015, Cell.

[20]  T. Olds,et al.  Anthropometrica : a textbook of body measurement for sports and health courses , 1996 .

[21]  Ching-Lai Hwang,et al.  Methods for Multiple Attribute Decision Making , 1981 .

[22]  Jurgita Antucheviciene,et al.  Measuring Congruence of Ranking Results Applying Particular MCDM Methods , 2011, Informatica.

[23]  Kevin Norton,et al.  Measurement techniques in anthropometry , 1996 .

[24]  R. Forthofer,et al.  Rank Correlation Methods , 1981 .

[25]  Seyed Hossein Razavi Hajiagha,et al.  Maximizing and minimizing sets in solving fuzzy linear programming , 2014 .

[26]  Morteza Yazdani,et al.  A state-of the-art survey of TOPSIS applications , 2012, Expert Syst. Appl..

[27]  M. Supej,et al.  Impact of Fatigue on the Position of the Release Arm and Shoulder Girdle over a Longer Shooting Distance for an Elite Basketball Player , 2009, Journal of strength and conditioning research.

[28]  J. A. Martínez,et al.  A stakeholder assessment of basketball player evaluation metrics , 2011 .

[29]  Mikael Collan,et al.  A multi-expert system for ranking patents: An approach based on fuzzy pay-off distributions and a TOPSIS-AHP framework , 2013, Expert Syst. Appl..

[30]  Jian-Bo Yang,et al.  Multiple Attribute Decision Making , 1998 .

[31]  D. Stec The personification of an object and the emergence of coaching , 2012 .

[32]  J E Cotes,et al.  Lung volumes and forced ventilatory flows. Report Working Party Standardization of Lung Function Tests, European Community for Steel and Coal. Official Statement of the European Respiratory Society. , 1993, The European respiratory journal. Supplement.

[33]  V. Genrea,et al.  Combining expert forecasts : Can anything beat the simple average ? , 2012 .

[34]  Paavo V. Komi,et al.  A simple method for measurement of mechanical power in jumping , 2004, European Journal of Applied Physiology and Occupational Physiology.

[35]  Patricia A. Adler,et al.  Intense Loyalty in Organizations: A Case Study of College Athletics. , 1988 .