Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings - 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020 |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (elektronisch) | 9781728195810 |
| ISBN (Print) | 978-1-7281-9582-7 |
| Publikationsstatus | Veröffentlicht - 2020 |
| Veranstaltung | 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020 - Virtual, Krakow, Polen Dauer: 23 Sept. 2020 → 25 Sept. 2020 |
Publikationsreihe
| Name | Proceedings - 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020 |
|---|
Abstract
In this work, we statistically analyze publicly available data on the health-related absenteeism of German professional football players and, outgoing from this, develop a machine-learning model for a prognosis of the probability that a player will have a longer health problem during the current season. That prognosis is essential for German insurance companies, since a short illness or injury is covered by the health insurance, whereas a longer absenteeism (over six weeks) is covered by a special insurance. Insurance companies have to calculate the risk for that special case in order offer an appropriate insurance rate. Our model gives an assessment of the risk, and thus plays a vital role in the calculation of the insurance rate that can be offered to a professional football player.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Informatik (insg.)
- Signalverarbeitung
- Mathematik (insg.)
- Steuerung und Optimierung
Zitieren
- Standard
- Harvard
- Apa
- Vancouver
- BibTex
- RIS
Proceedings - 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9291355 (Proceedings - 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Prognosis of health-related unavailability of professional german football players
AU - Schestakov, Stefan
AU - Becker, Matthias
PY - 2020
Y1 - 2020
N2 - In this work, we statistically analyze publicly available data on the health-related absenteeism of German professional football players and, outgoing from this, develop a machine-learning model for a prognosis of the probability that a player will have a longer health problem during the current season. That prognosis is essential for German insurance companies, since a short illness or injury is covered by the health insurance, whereas a longer absenteeism (over six weeks) is covered by a special insurance. Insurance companies have to calculate the risk for that special case in order offer an appropriate insurance rate. Our model gives an assessment of the risk, and thus plays a vital role in the calculation of the insurance rate that can be offered to a professional football player.
AB - In this work, we statistically analyze publicly available data on the health-related absenteeism of German professional football players and, outgoing from this, develop a machine-learning model for a prognosis of the probability that a player will have a longer health problem during the current season. That prognosis is essential for German insurance companies, since a short illness or injury is covered by the health insurance, whereas a longer absenteeism (over six weeks) is covered by a special insurance. Insurance companies have to calculate the risk for that special case in order offer an appropriate insurance rate. Our model gives an assessment of the risk, and thus plays a vital role in the calculation of the insurance rate that can be offered to a professional football player.
KW - Football player
KW - Injury
KW - Machine learning
KW - Statistical analysis
UR - http://www.scopus.com/inward/record.url?scp=85099238930&partnerID=8YFLogxK
U2 - 10.1109/EBCCSP51266.2020.9291355
DO - 10.1109/EBCCSP51266.2020.9291355
M3 - Conference contribution
AN - SCOPUS:85099238930
SN - 978-1-7281-9582-7
T3 - Proceedings - 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020
BT - Proceedings - 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Event-Based Control, Communication and Signal Processing, EBCCSP 2020
Y2 - 23 September 2020 through 25 September 2020
ER -