Having logged in using the betfair function, the environment contains the events method. This method can be used to get events and the number of markets for each event, when the event start, as well as other data that may be of interest.
bf$events(filter = marketFilter())| param | details |
|---|---|
filter |
select desired markets, see marketFilter for various parameters to filter by, or the relevant help pages on Betfair. If nothing is entered, all events are returned |
The function returns a dataframe of events (eg. Manchester United vs Arsenal), with data about the number of markets, start time, etc, a full list below:
| variable | details |
|---|---|
event_id |
the event id |
event_name |
the event name (eg. Manchester United vs Arsenal) |
event_countryCode |
the ISO-2 code, ISO-2 codes are available on wiki, examples include GB, IE, US, etc |
event_timezone |
the timezone in which the event is happening |
event_venue |
the event venue (if applicable) |
event_openDate |
the scheduled start of the event (format “YYYY-MM-DDT00:00:00.000Z”) |
marketCount |
number of markets associated with this country |
library(betfaiR)
# login
bf <- betfair(usr = Sys.getenv("bf_usr"),
pwd = Sys.getenv("bf_pwd"),
key = Sys.getenv("bf_key"))Login successful# return all countries
tmp <- bf$events()
head(tmp) event_id event_name event_timezone
1 28086700 Hradec Kralove v Prostejov Europe/London
2 28086701 Opava v Vitkovice Europe/London
3 28086702 Vysocina Jihlava v Vlasim Europe/London
4 28086703 Vitosha Bistritsa v PFC Hebar (Pazardzhik) Europe/London
5 28086698 Boca Juniors v San Lorenzo Europe/London
6 28086699 Pardubice v Dukla Prague Europe/London
event_openDate marketCount event_countryCode event_venue
1 2017-01-25T09:00:00.000Z 24 <NA> <NA>
2 2017-01-25T10:00:00.000Z 24 <NA> <NA>
3 2017-01-25T12:00:00.000Z 24 <NA> <NA>
4 2017-01-25T12:00:00.000Z 24 <NA> <NA>
5 2017-01-25T01:10:00.000Z 24 AR <NA>
6 2017-01-25T10:00:00.000Z 24 <NA> <NA># return all horse racing events
tmp <- bf$events(filter = marketFilter(eventTypeIds = 7))
head(tmp) event_id event_name event_countryCode event_timezone
1 28073772 Newb 11th Feb GB Europe/London
2 28074030 Donc 28th Jan GB Europe/London
3 28061486 Chelt 14th Mar GB Europe/London
4 28061487 Chelt 15th Mar GB Europe/London
5 28086841 Laun (AUS) 25th Jan AU Australia/Sydney
6 27999667 Del Mar (US) 4th Nov US US/Eastern
event_openDate marketCount event_venue
1 2017-02-11T15:35:00.000Z 1 <NA>
2 2017-01-28T15:40:00.000Z 1 <NA>
3 2017-03-14T13:30:00.000Z 13 <NA>
4 2017-03-15T13:30:00.000Z 11 <NA>
5 2017-01-25T06:55:00.000Z 18 Launceston
6 2017-11-03T04:00:00.000Z 1 <NA># return all horse racing events whose start date is beyond next week
tmp <- bf$events(filter = marketFilter(eventTypeIds = 7, from = Sys.Date() + 7))
head(tmp) event_id event_name event_countryCode event_timezone
1 28073772 Newb 11th Feb GB Europe/London
2 28061486 Chelt 14th Mar GB Europe/London
3 28061487 Chelt 15th Mar GB Europe/London
4 27999667 Del Mar (US) 4th Nov US US/Eastern
5 28074870 Leop 12th Feb IE Europe/London
6 28061488 Chelt 16th Mar GB Europe/London
event_openDate marketCount
1 2017-02-11T15:35:00.000Z 1
2 2017-03-14T13:30:00.000Z 13
3 2017-03-15T13:30:00.000Z 11
4 2017-11-03T04:00:00.000Z 1
5 2017-02-12T15:00:00.000Z 1
6 2017-03-16T13:30:00.000Z 10