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.
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).
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.