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Compute new classement for a set of players and reports upward/downward movements.

Source: R/players.new.classement.R
players.new.classement.Rd

Two new columns are added to the supplied data frame: classement_new (the updated classement) and classement_diff (the integer movement between old and new classement).

Usage

players.new.classement(
  players_df = players_m,
  classement_col = "classement",
  ranking_col = "position_bis",
  ordre = c("NC", "E6", "E4", "E2", "E0", "D6", "D4", "D2", "D0", "C6", "C4", "C2", "C0",
    "B6", "B4", "B2")
)

Arguments

players_df

A data frame of players. Defaults to players_m.

classement_col

Column name containing the current classement (default "classement")

ranking_col

Column name containing the current ranking (default "position_bis").

ordre

Vector of ordered classements to be considered.

Value

A data frame identical to players_df but with two additional columns:

classement_new

The newly computed classement.

classement_diff

Integer difference between new and old classement.

Two attributes are also attached to the returned data frame and displayed:

"transition_table"

Contingency table of old vs new classement.

"diff_table"

Contingency table of integer differences.

Details

In addition to these two columns, the function also constructs transition and difference tables (via classement.transitions). These tables are attached as attributes "transition_table" and "diff_table" to the returned data frame, and displayed to the console.

Players with classement "A", "B0", or with position_bis == "Inactive" are excluded from the computation and receive NA for both classement_new and classement_diff.

Examples

if (FALSE) { # \dontrun{
# Default: full dataset of players i.e. players_m
res <- players.new.classement()

# Subset example: by club 
players_N051 <- subset(players_m, club == "N051")
resN051 <- players.new.classement(players_N051)
} # }