Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis

Aychew Kassa Belete; Fasiledes Fetene Asfaw; Birhan Ambachew Taye; Bantie Getinet Yirsaw

doi:doi:10.11648/j.ijsspe.20240903.11

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Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis

Aychew Kassa Belete^*

, Fasiledes Fetene Asfaw, Birhan Ambachew Taye

, Bantie Getinet Yirsaw

Published in International Journal of Sports Science and Physical Education (Volume 9, Issue 3)

Received: 14 May 2024 Accepted: 12 June 2024 Published: 6 August 2024

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Abstract

Background: Sport injury is an injury which is occurs in playing field maybe in training or competition. Epidemiology of sports injury on male footballer has been documented that injury incidences were 10-35 injuries per 1000 game hours. The main objective of our study is predicting the number of injuries for coming specific time by analyzing historical injury data obtained from team physicians. Methods: We collected historical injury data from the Ethiopia Premier League which is collected for 50 weeks, including the number of injuries, types of injuries, affected players, and duration of absence from play. We then selected an appropriate time series model for forecasting injuries based on the nature of the data and its patterns, considering potential models such as ARIMA (AutoRegressive Integrated Moving Average). After training the selected time series model using historical injury data and validating its performance by comparing predicted values with actual injury occurrences, we used it to forecast injuries for the upcoming seasons of the Ethiopia Premier League. Results: In Ethiopia the weekly average increment in sport injury from week 1to week 50 was 4.4. The maximum number of sport injury occurred on week 30. The series is not stationary at level, but the series is stationary at first difference. The selected model in this study was ARIMA (3,0,0) that has small AIC and BIC. Based on ARIMA (3,0,0) model the new sport injury in Ethiopia premier league was 13 injuries in week 51, and the forecasted number of injuries for the following weeks were 12, 12, 13, 11, 11, 10, 10, 10, and 10, respectively, up to week 60. Conclusion: our research finding indicates that, occurrence of sport injury will increase for coming weeks so that teams should implement injury prevention programs, prioritize rest and recovery, and ensure access to qualified medical staff for immediate care and rehabilitation.

Published in	International Journal of Sports Science and Physical Education (Volume 9, Issue 3)
DOI	10.11648/j.ijsspe.20240903.11
Page(s)	40-46
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Sport Injury, Forecasting, Football, Autoregressive Integrative Moving Average

References

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APA Style

Belete, A. K., Asfaw, F. F., Taye, B. A., Yirsaw, B. G. (2024). Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis. International Journal of Sports Science and Physical Education, 9(3), 40-46. https://doi.org/10.11648/j.ijsspe.20240903.11

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ACS Style

Belete, A. K.; Asfaw, F. F.; Taye, B. A.; Yirsaw, B. G. Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis. Int. J. Sports Sci. Phys. Educ. 2024, 9(3), 40-46. doi: 10.11648/j.ijsspe.20240903.11

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AMA Style

Belete AK, Asfaw FF, Taye BA, Yirsaw BG. Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis. Int J Sports Sci Phys Educ. 2024;9(3):40-46. doi: 10.11648/j.ijsspe.20240903.11

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@article{10.11648/j.ijsspe.20240903.11,
  author = {Aychew Kassa Belete and Fasiledes Fetene Asfaw and Birhan Ambachew Taye and Bantie Getinet Yirsaw},
  title = {Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis
},
  journal = {International Journal of Sports Science and Physical Education},
  volume = {9},
  number = {3},
  pages = {40-46},
  doi = {10.11648/j.ijsspe.20240903.11},
  url = {https://doi.org/10.11648/j.ijsspe.20240903.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsspe.20240903.11},
  abstract = {Background: Sport injury is an injury which is occurs in playing field maybe in training or competition. Epidemiology of sports injury on male footballer has been documented that injury incidences were 10-35 injuries per 1000 game hours. The main objective of our study is predicting the number of injuries for coming specific time by analyzing historical injury data obtained from team physicians. Methods: We collected historical injury data from the Ethiopia Premier League which is collected for 50 weeks, including the number of injuries, types of injuries, affected players, and duration of absence from play. We then selected an appropriate time series model for forecasting injuries based on the nature of the data and its patterns, considering potential models such as ARIMA (AutoRegressive Integrated Moving Average). After training the selected time series model using historical injury data and validating its performance by comparing predicted values with actual injury occurrences, we used it to forecast injuries for the upcoming seasons of the Ethiopia Premier League. Results: In Ethiopia the weekly average increment in sport injury from week 1to week 50 was 4.4. The maximum number of sport injury occurred on week 30. The series is not stationary at level, but the series is stationary at first difference. The selected model in this study was ARIMA (3,0,0) that has small AIC and BIC. Based on ARIMA (3,0,0) model the new sport injury in Ethiopia premier league was 13 injuries in week 51, and the forecasted number of injuries for the following weeks were 12, 12, 13, 11, 11, 10, 10, 10, and 10, respectively, up to week 60. Conclusion: our research finding indicates that, occurrence of sport injury will increase for coming weeks so that teams should implement injury prevention programs, prioritize rest and recovery, and ensure access to qualified medical staff for immediate care and rehabilitation.
},
 year = {2024}
}

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TY  - JOUR
T1  - Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis

AU  - Aychew Kassa Belete
AU  - Fasiledes Fetene Asfaw
AU  - Birhan Ambachew Taye
AU  - Bantie Getinet Yirsaw
Y1  - 2024/08/06
PY  - 2024
N1  - https://doi.org/10.11648/j.ijsspe.20240903.11
DO  - 10.11648/j.ijsspe.20240903.11
T2  - International Journal of Sports Science and Physical Education
JF  - International Journal of Sports Science and Physical Education
JO  - International Journal of Sports Science and Physical Education
SP  - 40
EP  - 46
PB  - Science Publishing Group
SN  - 2575-1611
UR  - https://doi.org/10.11648/j.ijsspe.20240903.11
AB  - Background: Sport injury is an injury which is occurs in playing field maybe in training or competition. Epidemiology of sports injury on male footballer has been documented that injury incidences were 10-35 injuries per 1000 game hours. The main objective of our study is predicting the number of injuries for coming specific time by analyzing historical injury data obtained from team physicians. Methods: We collected historical injury data from the Ethiopia Premier League which is collected for 50 weeks, including the number of injuries, types of injuries, affected players, and duration of absence from play. We then selected an appropriate time series model for forecasting injuries based on the nature of the data and its patterns, considering potential models such as ARIMA (AutoRegressive Integrated Moving Average). After training the selected time series model using historical injury data and validating its performance by comparing predicted values with actual injury occurrences, we used it to forecast injuries for the upcoming seasons of the Ethiopia Premier League. Results: In Ethiopia the weekly average increment in sport injury from week 1to week 50 was 4.4. The maximum number of sport injury occurred on week 30. The series is not stationary at level, but the series is stationary at first difference. The selected model in this study was ARIMA (3,0,0) that has small AIC and BIC. Based on ARIMA (3,0,0) model the new sport injury in Ethiopia premier league was 13 injuries in week 51, and the forecasted number of injuries for the following weeks were 12, 12, 13, 11, 11, 10, 10, 10, and 10, respectively, up to week 60. Conclusion: our research finding indicates that, occurrence of sport injury will increase for coming weeks so that teams should implement injury prevention programs, prioritize rest and recovery, and ensure access to qualified medical staff for immediate care and rehabilitation.

VL  - 9
IS  - 3
ER  -

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Author Information

Aychew Kassa Belete

Department of Sport Science, Faculty of Natural and Computational Science, Woldia University, Woldia, Ethiopia

Contact Email

http://orcid.org/0009-0006-5195-5255
Fasiledes Fetene Asfaw

Department of Statistics, Faculty of Natural and Computational Science, Woldia University, Woldia, Ethiopia
Birhan Ambachew Taye

Department of Statistics, Faculty of Natural and Computational Science, Woldia University, Woldia, Ethiopia

Contact Email

http://orcid.org/0000-0002-2789-9963
Bantie Getinet Yirsaw

Department of Epidemiology of Biostatistics, University of Gondar, Gondar, Ethiopia

Contact Email

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Plain Text BibTeX RIS

APA Style

Belete, A. K., Asfaw, F. F., Taye, B. A., Yirsaw, B. G. (2024). Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis. International Journal of Sports Science and Physical Education, 9(3), 40-46. https://doi.org/10.11648/j.ijsspe.20240903.11

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ACS Style

Belete, A. K.; Asfaw, F. F.; Taye, B. A.; Yirsaw, B. G. Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis. Int. J. Sports Sci. Phys. Educ. 2024, 9(3), 40-46. doi: 10.11648/j.ijsspe.20240903.11

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AMA Style

Belete AK, Asfaw FF, Taye BA, Yirsaw BG. Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis. Int J Sports Sci Phys Educ. 2024;9(3):40-46. doi: 10.11648/j.ijsspe.20240903.11

Copy | Download

@article{10.11648/j.ijsspe.20240903.11,
  author = {Aychew Kassa Belete and Fasiledes Fetene Asfaw and Birhan Ambachew Taye and Bantie Getinet Yirsaw},
  title = {Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis
},
  journal = {International Journal of Sports Science and Physical Education},
  volume = {9},
  number = {3},
  pages = {40-46},
  doi = {10.11648/j.ijsspe.20240903.11},
  url = {https://doi.org/10.11648/j.ijsspe.20240903.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsspe.20240903.11},
  abstract = {Background: Sport injury is an injury which is occurs in playing field maybe in training or competition. Epidemiology of sports injury on male footballer has been documented that injury incidences were 10-35 injuries per 1000 game hours. The main objective of our study is predicting the number of injuries for coming specific time by analyzing historical injury data obtained from team physicians. Methods: We collected historical injury data from the Ethiopia Premier League which is collected for 50 weeks, including the number of injuries, types of injuries, affected players, and duration of absence from play. We then selected an appropriate time series model for forecasting injuries based on the nature of the data and its patterns, considering potential models such as ARIMA (AutoRegressive Integrated Moving Average). After training the selected time series model using historical injury data and validating its performance by comparing predicted values with actual injury occurrences, we used it to forecast injuries for the upcoming seasons of the Ethiopia Premier League. Results: In Ethiopia the weekly average increment in sport injury from week 1to week 50 was 4.4. The maximum number of sport injury occurred on week 30. The series is not stationary at level, but the series is stationary at first difference. The selected model in this study was ARIMA (3,0,0) that has small AIC and BIC. Based on ARIMA (3,0,0) model the new sport injury in Ethiopia premier league was 13 injuries in week 51, and the forecasted number of injuries for the following weeks were 12, 12, 13, 11, 11, 10, 10, 10, and 10, respectively, up to week 60. Conclusion: our research finding indicates that, occurrence of sport injury will increase for coming weeks so that teams should implement injury prevention programs, prioritize rest and recovery, and ensure access to qualified medical staff for immediate care and rehabilitation.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis

AU  - Aychew Kassa Belete
AU  - Fasiledes Fetene Asfaw
AU  - Birhan Ambachew Taye
AU  - Bantie Getinet Yirsaw
Y1  - 2024/08/06
PY  - 2024
N1  - https://doi.org/10.11648/j.ijsspe.20240903.11
DO  - 10.11648/j.ijsspe.20240903.11
T2  - International Journal of Sports Science and Physical Education
JF  - International Journal of Sports Science and Physical Education
JO  - International Journal of Sports Science and Physical Education
SP  - 40
EP  - 46
PB  - Science Publishing Group
SN  - 2575-1611
UR  - https://doi.org/10.11648/j.ijsspe.20240903.11
AB  - Background: Sport injury is an injury which is occurs in playing field maybe in training or competition. Epidemiology of sports injury on male footballer has been documented that injury incidences were 10-35 injuries per 1000 game hours. The main objective of our study is predicting the number of injuries for coming specific time by analyzing historical injury data obtained from team physicians. Methods: We collected historical injury data from the Ethiopia Premier League which is collected for 50 weeks, including the number of injuries, types of injuries, affected players, and duration of absence from play. We then selected an appropriate time series model for forecasting injuries based on the nature of the data and its patterns, considering potential models such as ARIMA (AutoRegressive Integrated Moving Average). After training the selected time series model using historical injury data and validating its performance by comparing predicted values with actual injury occurrences, we used it to forecast injuries for the upcoming seasons of the Ethiopia Premier League. Results: In Ethiopia the weekly average increment in sport injury from week 1to week 50 was 4.4. The maximum number of sport injury occurred on week 30. The series is not stationary at level, but the series is stationary at first difference. The selected model in this study was ARIMA (3,0,0) that has small AIC and BIC. Based on ARIMA (3,0,0) model the new sport injury in Ethiopia premier league was 13 injuries in week 51, and the forecasted number of injuries for the following weeks were 12, 12, 13, 11, 11, 10, 10, 10, and 10, respectively, up to week 60. Conclusion: our research finding indicates that, occurrence of sport injury will increase for coming weeks so that teams should implement injury prevention programs, prioritize rest and recovery, and ensure access to qualified medical staff for immediate care and rehabilitation.

VL  - 9
IS  - 3
ER  -

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