servevolleyR

Simulate many sets between two players given a number of parameters, that include probability of each player winning a point on their first serve, on their second serve, and the probability that their first serve will go in. This function returns a detailed list with data about the games within each simulated set.

Usage

simSets(n = 1000, pA, pB,
        playTiebreak = TRUE, players = c("A", "B"),
        p2A = NULL, firstServeA = NULL,
        p2B = NULL, firstServeB = NULL,
        .progress = "none")

Arguments

param	details
n	number of simulations (default is 1000)
pA	probability of player A winning point on their first serve
pB	probability of player B winning point on their first serve
playTiebreak	play tiebreak in the event the set reaches 6 games all
players	player names (vector of length 2)
p2A	probability of player A winning point on their second serve
firstServeA	probability of player A’s first serve being in
p2A	probability of player B winning point on their second serve
firstServeB	probability of player B’s first serve being in
.progress	`plyr`’s progress bar

Return

Unlike using replicate on simSet, using simSets will return a detailed list, containing data about the simulated sets rather than just the results of those simulations.

Methods

There are a number of generic methods available for an object returned by simSets, these are print, summary and plot, example use is show below.

Example

egSets <- simSets(n = 100,
                  pA = .78, pB = .70, p2A = .56, p2B = .6,
                  firstServeA = .67, firstServeB = .7)

The object egSets has a class of svR_sets which comes with a few methods

egSets

## 
## Simulation of 100 sets:
## 
## Server Probabilities:
##  player    p   p2 firstServe
##       A 0.78 0.56       0.67
##       B 0.70 0.60       0.70
## 
## Player A (A) won 0.63 of sets.

summary(egSets)

## 
## Simulation of 100 sets:
## 
## Server Probabilities:
##  player    p   p2 firstServe
##       A 0.78 0.56       0.67
##       B 0.70 0.60       0.70
## 
## Player A (A) won 0.63 of sets.
##        playerB
## playerA    1    2    3    4    5    6    7
##       2                          0.02     
##       3                          0.01     
##       4                          0.09     
##       5                               0.09
##       6 0.03 0.02 0.27 0.05           0.16
##       7                     0.09 0.17

plot(egSets)

Using `simDf`

If detail = TRUE then the list can also be entered into the function simDf which will convert the simulated sets into a dataframe.

df <- simDf(egSets)
head(df)

##   simNo pA pB setA setB set_res gameNo serving    p   p2 firstServe
## 1     1  A  B    6    3       1      1       A 0.78 0.56       0.67
## 2     1  A  B    6    3       1      2       B 0.70 0.60       0.70
## 3     1  A  B    6    3       1      3       A 0.78 0.56       0.67
## 4     1  A  B    6    3       1      4       B 0.70 0.60       0.70
## 5     1  A  B    6    3       1      5       A 0.78 0.56       0.67
## 6     1  A  B    6    3       1      6       B 0.70 0.60       0.70
##   game_res server returner
## 1        1      4        1
## 2        1      4        2
## 3        1      4        0
## 4        1      4        0
## 5        1      4        2
## 6        0      1        4

The dataset contains the following variables:

variables	about
simNo	simulation number
pA	player A
pB	player B
setA	games won by player A
setB	games won by player B
set_res	set result (1 if player A wins, 0 if player B wins)
gameNo	game number in set
serving	player serving
p	probability of server winning a point on their first serve
p2	probability of server winning a point on their second serve
firstServe	probability of first serve being in
game_res	game result (1 if server wins, 0 if returner wins)
server	number of points won by server in service game
returner	number of points won by returner in service game