vs_simulate_set: Simulate a set of volleyball
In openvolley/volleysim: Volleyball Match Simulation Tools

View source: R/simulate.R

vs_simulate_set

R Documentation

Simulate a set of volleyball

Description

vs_simulate_set_theor and vs_simulate_set_mc are convenience functions for vs_simulate_set(..., method = "theoretical") and vs_simulate_set(..., method = "monte carlo") respectively.

Usage

vs_simulate_set(
  rates,
  process_model = "phase",
  serving = NA,
  go_to = 25,
  point_margin = 2,
  simple = FALSE,
  id = NULL,
  method = "theoretical"
)

vs_simulate_set_mc(...)

vs_simulate_set_theor(...)

Arguments

`rates`	list: A two-element list, each element of which is a set of rates as returned by `vs_estimate_rates`. Experimental: for `process_model` "sideout", the `sideout` rate component can be a function. This function will be called at each step of the simulation with the parameters: `team_1_score` - the score of team 1 at each point in the set so far `team_2_score` - the score of team 2 at each point in the set so far `team_1_rotation` - the rotation of team 1 at each point in the set so far (rotations are counted relative to the team's starting rotation, which is 1) `team_2_rotation` - the rotation of team 2 at each point in the set so far (rotations are counted relative to the team's starting rotation, which is 1) `serving` - the serving team 1 or 2 at each point in the set so far `point_won_by` - which team won each point in the set so far (this will be NA for the last entry, because that's the current point that hasn't been simulated yet) `outcome` - the outcome of each point in the set so far, either "Sideout" or "Breakpoint" if `process_model` is "sideout", or details TBD if `process_model` is "phase" The function should return the sideout rate of the receiving team.
`process_model`	string: either "sideout" or "phase". The "sideout" model uses the estimated sideout rates (in the `rates` object) directly. The "phase" model breaks play down into different phases (serve, serve receive, etc) and uses the rates associated with those separate phases
`serving`	logical: if `TRUE`, team 1 will serve first. If `NA`, the team serving first will be chosen at random
`go_to`	integer: the minimum score that must be reached to end the set (typically 25 for indoor volleyball in sets 1 to 4, 15 in set 5, or 21 in beach volleyball)
`point_margin`	integer: the minimum score difference in order to win the set. Only applicable to `method` "monte carlo". For `method` "theoretical" a two-point margin is always used
`simple`	logical: if `TRUE`, return simplified output. Only applicable to `method` "monte carlo". If `simple = TRUE`, return the team (1 or 2) that won the set. If `simple = FALSE`, return extra details in a data.frame
`id`	: an optional value that (if non-`NULL`) will be returned in the `id` column of the returned data frame, if `simple` is `FALSE`
`method`	string: the simulation method to use. Either "monte carlo" or "theoretical". Details TBD
`...`	: parameters as for `vs_simulate_set`. `vs_simulate_set_theor` and `vs_simulate_set_mc` are convenience functions for `vs_simulate_set(..., method = "theoretical")` and `vs_simulate_set(..., method = "monte carlo")` respectively

Value

Integer (1 or 2) or a data frame, depending on the value of simple

Examples

## Not run: 
  library(datavolley)
  x <- dv_read(dv_example_file())
  rates <- vs_estimate_rates(x, target_team = "each")

  vs_simulate_set(rates) ## simulate a single set
  vs_simulate_match(rates) ## simulate a match
  ## so given the performances of the two teams during that match, we expect
  ##  that the home team should have won, with 3-0 being the most likely scoreline

  ## compare to the actual match result
  summary(x)

## End(Not run)

## sideout rates as a function for team 2
sofun2 <- function(serving, point_won_by, ...) {
    ## if team 2 won their previous sideout opportunity, their sideout rate is 0.6
    ## otherwise it's 0.5
    prevso <- tail(na.omit(point_won_by[serving == 1]), 1)
    if (length(prevso) < 1 || prevso == 1) {
        ## first sideout opportunity or lost the last one
        0.5
    } else {
        0.6
    }
}

rates <- list(list(sideout = 0.55), ## first team has constant 55% sideout rate
               list(sideout = sofun2)) ## function for team 2's sideout rate

## need to use method = "monte carlo" for this
vs_simulate_set(rates = rates, process_model = "sideout", method = "monte carlo")

openvolley/volleysim documentation built on Nov. 30, 2023, 12:49 a.m.