The balancedteams R package offers a suite of methods — currently two — including a greedy heuristic algorithm as well as a mixed integer linear programming algorithm (Schumacher 2022) that creates a “balanced” set of team assignments according to player scores and, optionally, accounting for a strata indicator. There are a number of ways to come up with this score but common methods used by our collaborators include an average of a self-survey and/or a captain’s assessment of a player’s athleticism.
You can install the development version of balancedteams from github with:
devtools::install_github("apeterson91/balancedteams)This is a basic example which shows you the basic input and output data structures as well as the package syntax.
library(balancedteams)
library(dplyr)head(mens_team)
#> group_id player_id num_players player_score
#> 1 1 1 1 33.33851
#> 2 2 2 1 60.36581
#> 3 3 3 1 44.16801
#> 4 4 4 1 53.94389
#> 5 5 5 1 56.59137
#> 6 6 6 1 42.08316team_config_one <- GenerateBalancedTeams(mens_team,
num_teams = 7,
max_num_team = 11,
method = "greedy")
GetMeanScore(team_config_one)
#> # A tibble: 7 × 4
#> team_id `Mean Score` `Median Score` `# Players`
#> <int> <dbl> <dbl> <int>
#> 1 1 44.2 42.1 11
#> 2 2 48.2 45.8 11
#> 3 3 54.0 52.8 11
#> 4 4 40.0 37.1 11
#> 5 5 51.6 49.7 11
#> 6 6 51.1 48.1 11
#> 7 7 56.1 56.2 11Please note that the balancedteams project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Schumacher, Dirk. 2022. Ompr: Model and Solve Mixed Integer Linear Programs. https://github.com/dirkschumacher/ompr.