Skip to main content

Predicting the Evolution of Sports Federation Membership: An Important Tool to Asses National Governing Bodies’ Strategic Planning

Camps, Andreu, Pappous, Athanasios (2016) Predicting the Evolution of Sports Federation Membership: An Important Tool to Asses National Governing Bodies’ Strategic Planning. Journal of Sports Science, 4 . pp. 57-69. ISSN 2332-7839. (doi:10.17265/2332-7839/2016.02.001) (KAR id:59408)

PDF
Language: English


Download (473kB) Preview
[thumbnail of Predicting the evolution of Sports Federation.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format
Official URL
http://dx.doi.org/10.17265/2332-7839/2016.02.001

Abstract

Quantifying the potential market of sports licenses is key in order for National Governing Bodies of sport (NGBs) to be able to design good strategic planning. We compared the classical methods of univariate prediction and the Autoregressive Integrated Moving Average (ARIMA) methods. Reliability of the available data was verified with the Time Series Regression with ARIMA Noise, Missing and Outliers (TRAMO) method, and the existence of a trend was verified using Daniel’s test. For the purposes of this study—the researches collected and analysed secondary data from a 40-year series in 45 sports in Spain covering a very long period of time in a variety of sport disciplines. The study shows that, with the available data, short-and mid-term forecasting is possible in a number of sports, but not in all of them. It also proves that Holt’s classical method of exponential smoothing is the one that yields best results. Golf, Basketball, Athletics and Hunting NGB show worrying prospects of decline levels and need an immediate change in the strategic plans. Other than for forecasting the evolution of athletes in the mid-term in order to improve strategic planning in NGBs, the present findings can be useful for public authorities to define their aid policies for NGBs, and they can also helpcompanies in the industry to anticipate market developments.

Item Type: Article
DOI/Identification number: 10.17265/2332-7839/2016.02.001
Uncontrolled keywords: Sports forecasting, ARIMA models, time series, market evolution, Sport Participation
Subjects: G Geography. Anthropology. Recreation > GV Recreation. Leisure > Sports sciences
Divisions: Divisions > Division of Natural Sciences > School of Sport and Exercise Sciences
Depositing User: Athanasios Pappous
Date Deposited: 03 Dec 2016 23:47 UTC
Last Modified: 16 Feb 2021 13:40 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/59408 (The current URI for this page, for reference purposes)
Pappous, Athanasios: https://orcid.org/0000-0002-2162-0239
  • Depositors only (login required):

Downloads

Downloads per month over past year