Plot risk matrices

Given an injds S3 object, it depicts risk matrix plots , a graph in which the injury incidence (frequency) is plotted against the average days lost per injury (consequence). The point estimate of injury incidence together with its confidence interval is plotted, according to the method used when running injsummary() function. On the y-axis, the mean time-loss per injury together with \(\pm\) IQR (days) is plotted. The number shown inside the point and the point size itself, report the injury burden (days lost per player-exposure time), the bigger the size the greater the burden. See References section.

Usage

gg_injriskmatrix(
  injds,
  var_type_injury = NULL,
  add_contour = TRUE,
  title = NULL,
  xlab = "Incidence (injuries per _)",
  ylab = "Mean time-loss (days) per injury",
  errh_height = 1,
  errv_width = 0.05,
  cont_max_x = NULL,
  cont_max_y = NULL,
  ...
)

Arguments

injds

injds S3 object (see injsummary())

var_type_injury

Character specifying the name of the column. A (categorical) variable referring to the "type of injury" (e.g. muscular/articular/others or overuse/not-overuse etc.) according to which visualize injury summary statistics (optional, defaults to NULL).

add_contour

Logical, whether or not to add contour lines of the product between injury incidence and mean severity (i.e. 'incidence x average time-loss'), which leads to injury burden (defaults to TRUE).

title

Text for the main title passed to ggplot2::ggtitle().

xlab

x-axis label to be passed to ggplot2::xlab().

ylab

y-axis label to be passed to ggplot2::ylab().

errh_height

Set the height of the horizontal interval whiskers; the height argument for ggplot2::geom_errorbarh().

errv_width

Set the width of the vertical interval whiskers; the width argument for
ggplot2::geom_errorbar().

cont_max_x, cont_max_y

Numerical (optional) values indicating the maximum on the x-axis and y-axis, respectively, to be reached by the contour.

...

Other arguments passed on to ggplot2::geom_contour() and metR::geom_text_contour(). These are often aesthetics like bins = 15 or breaks = 10.

Value

A ggplot object (to which optionally more layers can be added).

References

Bahr R, Clarsen B, Derman W, et al. International Olympic Committee consensus statement: methods for recording and reporting of epidemiological data on injury and illness in sport 2020 (including STROBE Extension for Sport Injury and Illness Surveillance (STROBE-SIIS)) British Journal of Sports Medicine 2020; 54:372-389.

Fuller C. W. (2018). Injury Risk (Burden), Risk Matrices and Risk Contours in Team Sports: A Review of Principles, Practices and Problems.Sports Medicine, 48(7), 1597–1606.
https://doi.org/10.1007/s40279-018-0913-5

Examples

# \donttest{
df_exposures <- prepare_exp(raw_df_exposures, player = "player_name",
                            date = "year", time_expo = "minutes_played")
df_injuries  <- prepare_inj(raw_df_injuries, player = "player_name",
                            date_injured = "from", date_recovered = "until")
injd         <- prepare_all(data_exposures = df_exposures,
                            data_injuries  = df_injuries,
                            exp_unit = "matches_minutes")
# }

# \donttest{
injds <- injsummary(injd)
#> Warning: 
#>   Exposure time unit is matches_minutes
#>   So... Injury incidence and injury burden are calculated per 100 player-matches of exposure (90 minutes times 100)
#> 
#> Warning: 
#>   Exposure time unit is matches_minutes
#>   So... Injury incidence and injury burden are calculated per 100 player-matches of exposure (90 minutes times 100)
#> 
injds2 <- injsummary(injd, var_type_injury = "injury_type")
#> Warning: 
#>   Exposure time unit is matches_minutes
#>   So... Injury incidence and injury burden are calculated per 100 player-matches of exposure (90 minutes times 100)
#> 
#> Warning: 
#>   Exposure time unit is matches_minutes
#>   So... Injury incidence and injury burden are calculated per 100 player-matches of exposure (90 minutes times 100)
#> 

gg_injriskmatrix(injds)

gg_injriskmatrix(injds2, var_type_injury = "injury_type", title = "Risk matrix")
#> Warning: An injury average time-loss is bigger than its 75% quartile
#>     time-loss. Possibly, there is a concrete long-term injury in the data.
#>     For plotting purposes the vertical upper limit (i.e. 75% quartile)
#>     is lengthened to the average value.

# }