raw_df_injuries: Minimal example of injury data

In injurytools: A Toolkit for Sports Injury Data Analysis

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.

injurytools documentation built on Nov. 15, 2023, 1:06 a.m.