Introduction
This vignette demonstrates how to leverage FastBreakR’s thin wrappers around the pbpstats API, developed by Daryl Blackport. This wrapper provides easy access to every endpoint of the pbpstats API — including live game data, play-by-play, team stats, player stats, and more. FastBreakR is the only R package offering a complete pbpstats API wrapper covering all available endpoints.
See https://api.pbpstats.com/docs for more info.
Load FastBreakR
# install.packages("remotes")
remotes::install_github("JesseKartes/FastBreakR", quiet = TRUE)
library(FastBreakR)
library(tibble, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)Get Career Stats for Teams/Players/Lineups
This thin wrapper make it easy to fetch comprehensive career statistics for any team, player, or lineup. This is particularly useful for building historical performance summaries or benchmarking entities against league averages.
# Fetch career stats for Tyrese Haliburton
season_stats <- get_all_season_stats(entity_type = "Player", entity_id = "1630169")
# View Hali's regular season career stats
player_stats <- tibble(season_stats$results$`Regular Season`) %>%
select(Season, GamesPlayed, PlusMinus, Points, FG3M)
knitr::kable(player_stats, caption = paste('Tyrese Haliburton Career Stats'))| Season | GamesPlayed | PlusMinus | Points | FG3M |
|---|---|---|---|---|
| 2020-21 | 58 | -179 | 753 | 121 |
| 2021-22 | 26 | -101 | 454 | 57 |
| 2021-22 | 51 | -225 | 727 | 104 |
| 2021-22 | 77 | -326 | 1181 | 161 |
| 2022-23 | 56 | -35 | 1160 | 161 |
| 2023-24 | 69 | 294 | 1389 | 195 |
| 2024-25 | 73 | 222 | 1359 | 218 |
Get Players Stats for Specific Lineups
Lineup analytics allow you to isolate the impact of specific player combinations. The snippet below retrieves stats for the 2024–25 Knicks playoff starting five, ideal for lineup evaluation or opponent scouting.
# Knicks Playoffs Starters
knicks_playoffs <- get_lineup_player_stats(
season = "2024-25",
season_type = "Playoffs",
lineup_id = "1626157-1628384-1628404-1628969-1628973"
)
knicks_stats <- tibble(knicks_playoffs$multi_row_table_data) %>%
select(Name, Minutes, PlusMinus, Points, FtPoints)
knitr::kable(knicks_stats, caption = '2024-25 Knicks Playoffs Starters')| Name | Minutes | PlusMinus | Points | FtPoints |
|---|---|---|---|---|
| Karl-Anthony Towns | 335 | -31 | 183 | 31 |
| OG Anunoby | 335 | -31 | 108 | 12 |
| Josh Hart | 335 | -31 | 100 | 27 |
| Mikal Bridges | 335 | -31 | 113 | 5 |
| Jalen Brunson | 335 | -31 | 236 | 59 |
Live Team and Player Stats
For live updates and streaming dashboards, pbpstats wrappers seamlessly pull in-game metrics. Here’s how to grab team-level live data from Game One of the 2024-25 NBA Finals.
# Game One 2024-25 NBA finals Live Stats
live_game <- get_live_game(game_id = "0042400401", result_type = "team")
live_stats <- head(live_game$game_data$rows, 10)
knitr::kable(live_stats, caption = paste('NBA Finals Game One'))| stat | home | visitor |
|---|---|---|
| Points | 110 | 111 |
| Possessions | 102 | 101 |
| Seconds Per Possession | 14.186 | 14.188 |
| Offensive Rating | 107.843 | 109.901 |
| True Shot Attempts | 109 | 92 |
| Shot Quality | 0.556 | 0.533 |
| eFG% | 0.454 | 0.585 |
| TS% | 0.505 | 0.603 |
| 2pt FG% | 0.412 (28/68) | 0.488 (21/43) |
| 3pt FG% | 0.367 (11/30) | 0.462 (18/39) |
Conclusion
In this vignette, we showcased FastBreakR’s pbpstats API wrapper across three simple use cases:
- Historical Career Analysis: Pull full career statistics for players, teams, or lineups to create performance summaries.
- Lineup-Specific Metrics: Evaluate the impact of specific player combinations.
- Real-Time Live Data: Integrate in-game team and player stats into dashboards or live analytics reports.
This is just a small glimpse of what’s possible with the pbpstats API. FastBreakR is the only R package with full pbpstats integration—bringing powerful, customizable NBA analytics to your workflow.