BAwiR (version 1.3.4)

do_four_factors_df: Four factors data frame

Description

This function computes team's offense and defense four factors. The four factors are Effective Field Goal Percentage (EFGP), Turnover Percentage (TOVP), Offensive Rebound Percentage (ORBP) and Free Throws Rate (FTRate). They are well defined at http://www.rawbw.com/~deano/articles/20040601_roboscout.htm and https://www.basketball-reference.com/about/factors.html.

As a summary, EFGP is a measure of shooting efficiency; TOVP is the percentage of possessions where the team missed the ball, see https://www.nba.com/thunder/news/stats101.html to read about the 0.44 coefficient; ORBP measures how many rebounds were offensive from the total of available rebounds; Finally, FTRate is a measure of both how often a team gets to the line and how often they make them.

Usage

do_four_factors_df(df_games, teams)

Value

A list with two data frames, df_rank and df_no_rank. Both have the same columns:

• Team: Team name.

• Type: Either Defense or Offense.

• EFGP, ORBP, TOVP and FTRate.

The df_rank data frame contains the team ranking label for each statistic between parentheses. Therefore, df_no_rank is used to create the ggplot with the numerical values and df_rank is used to add the ranking labels.

Arguments

df_games

Data frame with the games, players info, advanced stats and eventually recoded teams names.

teams

Teams names.

Author

Guillermo Vinue

Details

Instead of defining the Offensive and Defensive Rebound Percentage as mentioned in the previous links, I have computed just the Offensive Rebound Percentage for the team and for its rivals. This makes easier to have four facets, one per factor, in the ggplot.

In order to establish the team rankings, we have to consider these facts: In defense (accumulated statistics of the opponent teams to the team of interest), the best team in each factor is the one that allows the smallest EFGP, the biggest TOVP, the smallest ORBP and the smallest FTRate, respectively.

In offense (accumulated statistics of the team of interest), the best team in each factor is the one that has the biggest EFGP, the smallest TOVP, the biggest ORBP and the biggest FTRate, respectively.

See Also

get_four_factors_plot

Examples

df <- do_join_games_bio("ACB", acb_games_1718, acb_players_1718)
df1 <- do_add_adv_stats(df)
# When only one team is selected the rankings between parentheses
# do not reflect the real rankings regarding all the league teams.
# The rankings are computed with respect to the number of teams 
# passed as an argument.
df_four_factors <- do_four_factors_df(df1, "Valencia")