Getting started with sharpapi

What this package does

sharpapi wraps the SharpAPI REST API, which normalizes real-time sports betting odds from 45+ sportsbooks into one schema. Four functions cover the common cases:

Each returns a plain data frame, so the result goes straight into whatever you normally use — dplyr, data.table, base subsetting.

Setting your key

Every call needs an API key. A free tier is available at https://sharpapi.io. The package reads credentials from the SHARPAPI_KEY environment variable rather than function arguments. Avoid storing real keys in source files:

Sys.setenv(SHARPAPI_KEY = "your-key-here")

For anything beyond a one-off session, put it in ~/.Renviron instead (usethis::edit_r_environ() opens the file) so it is set for every session and stays out of your project directory:

SHARPAPI_KEY=your-key-here

If the variable is unset, every function stops with a message telling you so rather than making an unauthenticated request.

Which sports are live right now

library(sharpapi)

sports <- sharpapi_sports()
head(sports[order(-sports$live_count), c("id", "name", "event_count", "live_count")])

#>          id       name event_count live_count
#> 1    soccer     Soccer         812         37
#> 2  baseball   Baseball          51          4

Fetching odds

sharpapi_odds() passes any named argument through to the API as a filter. Useful ones are sport, league, sportsbook, market_type, is_live and limit:

odds <- sharpapi_odds(sport = "baseball", market_type = "moneyline", limit = 500)

str(odds[1, c("sportsbook", "home_team", "away_team", "selection", "odds_american")])

#> 'data.frame': 1 obs. of  5 variables:
#>  $ sportsbook   : chr "pinnacle"
#>  $ home_team    : chr "Yankees"
#>  $ away_team    : chr "Red Sox"
#>  $ selection    : chr "Yankees"
#>  $ odds_american: int -145

Because the result is a data frame, comparing one market across books is ordinary R:

best <- odds[odds$event_id == odds$event_id[1] & odds$selection == "Yankees", ]
best[order(-best$odds_decimal), c("sportsbook", "odds_american", "odds_decimal")]

Finding opportunities

sharpapi_arbitrage() (Hobby tier and above) returns cross-book arbitrage. The individual sides live in a nested legs column rather than as top-level fields:

arb <- sharpapi_arbitrage(sport = "baseball")
arb[, c("event_id", "market_type", "profit_percent")]

# the two sides of the first opportunity
arb$legs[[1]]

sharpapi_ev() (Pro tier and above) returns positive expected value bets, priced against the sharp reference books:

ev <- sharpapi_ev(sport = "baseball")
head(ev[order(-ev$ev_percentage), c("sportsbook", "selection", "ev_percentage")])

A key below the required tier raises an HTTP error rather than returning an empty frame, so wrap these in try() if you are probing what a key can reach.

Trying it without a key

If you want to work through the data shapes before signing up, sample snapshots (MLB and 2026 World Cup) are published as CSVs at https://github.com/Sharp-API/SharpAPI-Sample-Data. The snapshots use SharpAPI odds field names and provide offline examples for exploring the data. Live responses may include additional fields or nested objects:

url <- paste0(
  "https://raw.githubusercontent.com/Sharp-API/",
  "SharpAPI-Sample-Data/main/data/mlb_odds_snapshot.csv"
)
odds <- read.csv(url)

Errors

HTTP errors are raised by httr2 with the response status and API message. Common status codes include: