zipf_hcp: Handicap a race using many races

In durtal/RcappeR: Tools to aid the analysis and handicapping of Thoroughbred Horse Racing

Description

Assess and establish the performance of a winner by using the ratings from many different, but similar, races, calls zipf_race.

Usage

zipf_hcp(race, past_races, race_id, btn_var, rating = NULL,
  results = "detail", .progress = "none")

Arguments

race	dataframe of race to handicap
past_races	dataframe of past races used to handicap
race_id	name of variable to split past_races up by so each split is one race
btn_var	name of variable in race with margins between horses
rating	name of variable (if applicable) in past_races that contains the ratings of those runners
results	default detail, determines the output, other option is simple, which will return the mean rating.
.progress	plyr's progress bar (default = "none", options inc. "text", "time", "tk" or "win")

Details

The past_races dataframe is split according to race_id, so each split should be a small dataframe of a single race. For each of these races they are entered into the zipf_race function as race_2, while the race being handicapped is the race param. The return is a dataframe with the race_id and a rating for the winner of race based on the data from each race in past_races.

Value

Depending on param in results it either returns a solitary rating (the mean of all ratings returned), or a detailed list that can be analysed further, the list contains

• n_races number of races used

• mean_rtg mean rating for the race

• summary summary statistics of ratings returned

• ratings ratings dataframe (with vars race_id and zipf_rtg)

durtal/RcappeR documentation built on May 15, 2019, 6 p.m.