betfair.R

bf <- betfair(usr = Sys.getenv("BETFAIR_USR"),
              pwd = Sys.getenv("BETFAIR_PWD"),
              key = Sys.getenv("BETFAIR_KEY"))
              
outlist <- vector("list", 120)
for(i in 1:120) {
    # sleep for 60seconds
    Sys.sleep(60)
    # collect marketCatalogue data, contains team names
    tmp <- bf$marketCatalogue(filter = marketFilter(marketIds = "1.121198987"),
                              marketProjection = c("COMPETITION", "EVENT", "EVENT_TYPE", "RUNNER_DESCRIPTION"))
    
    # collect marketBook data, unparsed response from Betfair API
    tmp1 <- bf$marketBook(marketIds = "1.121198987")
    
    # extract runners, with price, totalMatched data
    runners <- tmp[[1]]$runners
    prices <- plyr::rbind.fill(lapply(1:length(tmp1$result[[1]]$runners), function(x) {
        data.frame(tmp1$result[[1]]$runners[[x]], time = Sys.time(), stringsAsFactors = FALSE)
    }))
    
    # merge two dataframes, by selectionId and place in list
    outlist[[i]] <- merge(x = runners,
                          y = subset(prices, select = -handicap),
                          by = "selectionId",
                          sort = F)

    print(i)
}

library(ggplot2)
derby <- plyr::ldply(outlist)

ggplot(derby, aes(x = time, y = 1 / lastPriceTraded, col = runnerName)) + 
    geom_point() + 
    geom_path() +
    scale_color_manual(values = c(fantasysocceR::team_pal(), "The Draw" = "#000000")) + 
    RcappeR::theme_rcapper() + 
    labs(title = "Man Utd vs Man City\n25/10/15") + 
    theme(plot.title = element_text(face = "bold"))