pinnacle.API

R Wrapper for the Pinnacle Sports API

The Pinnacle Sports ( www.pinnaclesports.com) manual can be found here :

http://www.pinnaclesports.com/en/api/manual

To use the Pinnacle Sports API you must have an account with Pinnacle Sports.

Please contact Pinnacle Sports directly at csd@pinnaclesports.com for all account questions. Pinnacle Terms & Conditions: http://www.pinnaclesports.com/en/termsandconditions

The API is not accessible from all IP-Ranges , especially IP addresses from the UK and the USA are Geo IP blocked.

To install the newest version :

devtools::install_github("marcoblume/pinnacle.API")

Or install a stable version from CRAN :

install.packages("pinnacle.API")

Example Code

library(pinnacle.API)
library(dplyr)
library(lubridate)

Please make sure that you understand the terms and conditions.

AcceptTermsAndConditions()

and then accept them. If AcceptTermsnAndConditions is not set to TRUE the functions will not run.

AcceptTermsAndConditions(TRUE)

Your credentials are the username and password for logging into www.pinnaclesports.com.

SetCredentials("MyUserName","MyPassWord")

Pull the Sport Data and filter out the leagues that have lines for Badminton available.

Sport_data <- GetSports() 
Badminton_ID <- Sport_data$SportID[Sport_data$SportName=="Badminton"]
League_data <- GetLeagues("Badminton")
active_leagues <- League_data %>% 
  filter(LinesAvailable == 1)
Badminton_League_Ids <- active_leagues$LeagueID

Use the showOddsDF() function to aggregate all the data into a nicer data.frame.

badminton_data <- showOddsDF(sportname = "Badminton" , Badminton_League_Ids )

Convert the dates into POSIX

## Convert Times to Posix
badminton_data$StartTime <- as.POSIXct(badminton_data$StartTime,format="%Y-%m-%dT%H:%M:%S",tz="UTC")
badminton_data$cutoff <- as.POSIXct(badminton_data$cutoff,format="%Y-%m-%dT%H:%M:%S",tz="UTC")

This DF has all the necessary IDs and information that you can then pass to the PlaceBet() function to place your wagers.

Examples for Filter Settings on Soccer Data

use the same code as above and change the Sport from Badminton to Soccer.

## Some Filter Suggestions to clean the Data 
soccer_filtered <- soccer_data %>% 
  ## Only Period "0" , the main period 
  filter(PeriodNumber == 0 ) %>% 
  ## No Live Games
  filter( LiveStatus != 1) %>% 
  ## No Corners
  filter(. , !grepl("Corner",HomeTeamName)) %>% 
  ## No Home vs Aways
  filter(. , !grepl("Home Team",HomeTeamName)) %>% 
  ## No advance Lines
  filter(. , !grepl("advance",HomeTeamName)) %>%
  ## No raise the cup lines
  filter(. , !grepl("raise",HomeTeamName)) %>% 
  ## Filter games past cutoff time
  filter(cutoff > as.POSIXlt(Sys.time(),tz="UTC")) %>%
  ## Filter games that are played in the next 24h
  filter(StartTime < as.POSIXlt(Sys.time(),tz="UTC")+hours(24) )

This is a filter Ideas for Live Games in Soccer. Modify showOddsDF() with ISLive= TRUE for a faster response if only Live Events are needed. The League IDs are retrieved using GetLeagues().

data <- showOddsDF(sportname = "Soccer" , Sport_Type_League_IDs , isLive = TRUE)

data %>%
      ## Only bet on Period "1"
      filter(PeriodNumber == 0 ) %>%
      ## No Live Games
      filter( LiveStatus == 1) %>%
      ## Specific
      filter(homeScore + awayScore == 3 ) %>%
      ## only 1st half
      filter(state == 1) %>%
      ## only from 17th min into state
      filter(elapsed  > 17)

To check all Running Wagers use GetBetsList() with betlist = "RUNNING". Below call will fetch all wagers that are RUNNING from the last 28 days.

 betlist <- GetBetsList(betlist = "RUNNING",
                         fromDate = as.POSIXlt(Sys.Date(), tz = "UTC") - 28 * 24 * 60 * 60,
                         toDate = as.POSIXlt(Sys.Date(), tz = "UTC") + 24 * 60 * 60)