| raw_df_injuries {injurytools} | R Documentation |
Minimal example of injury data
Description
An example of an injury data set containing minimum required injury
information as well as other further injury-related variables. It includes
Liverpool Football Club male's first team players' injury data. Each row
refers to player-injury. These data have been scrapped from
https://www.transfermarkt.com/ website using self-defined R code
with rvest and xml2 packages.
Usage
raw_df_injuries
Format
A data frame with 82 rows corresponding to 23 players and 11 variables:
- player_name
Name of the football player (factor)
- player_id
Identification number of the football player (factor)
- season
Season to which this player's entry corresponds (factor)
- from
Date of the injury of each data entry (Date)
- until
Date of the recovery of each data entry (Date)
- days_lost
Number of days lost due to injury (numeric)
- games_lost
Number of matches lost due to injury (numeric)
- injury
Injury specification as it appears in https://www.transfermarkt.com (character)
- injury_acl
Whether it is Anterior Cruciate Ligament (ACL) injury or not (NO_ACL)
- injury_type
A five level categorical variable indicating the type of injury, whether Bone, Concussion, Ligament, Muscle or Unknown; if any, NA otherwise (factor)
- injury_severity
A four level categorical variable indicating the severity of the injury (if any), whether Minor (<7 days lost), Moderate ([7, 28) days lost), Severe ([28, 84) days lost) or Very_severe (>=84 days lost); NA otherwise (factor)
Note
This data frame is provided for illustrative purposes. We warn that they might not be accurate, there might be a mismatch and non-completeness with what actually occurred. As such, its use cannot be recommended for epidemiological research (see also Hoenig et al., 2022).
Source
https://www.transfermarkt.com/
References
Hoenig, T., Edouard, P., Krause, M., Malhan, D., Relógio, A., Junge, A., & Hollander, K. (2022). Analysis of more than 20,000 injuries in European professional football by using a citizen science-based approach: An opportunity for epidemiological research?. Journal of science and medicine in sport, 25(4), 300-305.