raw_df_exposures {injurytools}

Minimal example of exposure data

Description

An example of a player exposure data set that contains minimum required exposure information as well as other player- and match-related variables. It includes Liverpool Football Club male's first team players' exposure data, exposure measured as (number or minutes of) matches played, over two consecutive seasons, 2017-2018 and 2018-2019. Each row refers to player-season. These data have been scrapped from https://www.transfermarkt.com/ website using self-defined R code with rvest and xml2 packages.

Usage

raw_df_exposures

Format

A data frame with 42 rows corresponding to 28 football players and 16 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)

year

Year in which each season started (numeric)

matches_played

Matches played by the player in each season (numeric)

minutes_played

Minutes played by the player in each season (numeric)

liga

Name of the ligue where the player played in each season (factor)

club_name

Name of the club to which the player belongs in each season (factor)

club_id

Identification number of the club to which the player belongs in each season (factor)

age

Age of the player in each season (numeric)

height

Height of the player in m (numeric)

place

Place of birth of each player (character)

citizenship

Citizenship of the player (factor)

position

Position of the player on the pitch (factor)

foot

Dominant leg of the player. One of both, left or right (factor)

goals

Number of goals scored by the player in that season (numeric)

assists

Number of assists provided by the player in that season (numerical)

yellows

Number of the yellow cards received by the player in that season (numeric)

reds

Number of the red cards received by the player in that season (numeric)

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.