Linear mathematical model to rate influence of home field factor in football

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PhD, Associate Professor V.N. Yushkin
Volgograd State Agrarian University, Volgograd

Objective of the study was to rate influence of the home field factor in football by a linear mathematical model, and offer theoretical and practical provisions for adaptation to the opponent’s field.
Methods and structure of the study. We analyzed for the modeling purposes practical performance of the national football teams in qualifiers for the 2020 European Football Championship from March 21, 2019 to November 19, 2019; and tested the linear mathematical model in the following two versions. Version 1 offered a system of equations with a constant ratio indicative of the home field factor influence. And linear mathematical model version 2 implies a mix of mini-groups (events), with a separate constant ratio of the home field influence for every group. The systems of linear equations were subject to numerical calculations to arrive to rating points. This linear mathematical model rating system may be recommended for application in every team sport.
Results and conclusion. The home field factor is known to influence the competitive performance and, hence, needs to be addressed by a special adaptation technology. Such a technology will set a range of special goals including identifying the teammates with the highest adaptability issues that undermine their must-wing mindsets. Such an adaptation technology will be implemented using customizable team/ individual training methods.

Keywords: rating, system, classification, modeling, mathematical model.

References

  1. Polozov A.A., Gazimova Z.F., Kraev M.V. Football Information Model on the Example of Russian Participation in 2018 World Cup. Human. Sport. Medicine, 2018, vol. 18, no 1, pp. 138-148.
  2. Polozov A.A., Suvorova E.A., Melnikova A.V., Korelina A.V., Mikhryakov S.V. Forecasting of results of the 2018 World Cup on the basis of a new algorithm of consolidation of data. Uchenye zapiski universiteta imeni P.F. Lesgafta, 2018, no 4, pp. 263-269.
  3. Sadovskiy L.E., Sadovskaya A.A. Reytingovye sistemy sportivnykh klassifikatciy [Rating systems for sports classifications]. Teoriya i praktika fizicheskoy kultury, 1988, no 8, pp. 27-29.
  4. Yushkin V.N. Sistema opredeleniya reytinga [The Ranking System]. Sovremennaya nauka: aktualnye problemy teorii i praktiki. Ser.: Gumanitarnye nauki, 2020, no 1, pp. 122-126.
  5. Karminsky A., Polozov A.A. Handbook of Ratings. Approaches to Ratings in the Economy, Sports, and Society, Springer International Publishing house, London, 2016. 360 p.
  6. Pollard R, Gómez M.A. Components of home advantage in 157 national soccer leagues worldwide. International Journal of Sport and Exercise Psychology, 2014, vol. 12, no 3, pp. 218-233.
  7. Mangan S., Collins K. A rating system for gaelic football teams: factors that influence success. International Journal of Computer Science in Sport, 2016, Volume 15, Issue 2, pp. 78-90.