CFB Data Stats Examples

Load and Install Packages

if (!requireNamespace('pak', quietly = TRUE)){
  install.packages('pak')
}
pak::pak(c("dplyr", "tidyr", "gt", "cfbfastR"))

## ℹ Loading metadata database

## ✔ Loading metadata database ... done

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## → Package library at /home/runner/work/_temp/Library.

## ✔ All system requirements are already installed.

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## ℹ No downloads are needed

## ℹ Installing system requirements

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## Reading package lists...

## ℹ Executing `sudo sh -c apt-get -y install libicu-dev libcurl4-openssl-dev libssl-dev cmake make libuv1-dev pandoc libnode-dev libxml2-dev`

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library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(tidyr)
library(gt)
library(cfbfastR)
# pak::pak("sportsdataverse/cfbfastR")

Settling 2019 LSU and 2013 Florida State offense debates

Get Season Statistics by Team

team_season_stats <- dplyr::bind_rows(
   cfbd_stats_season_team(year=2019, team = "LSU"),
   cfbd_stats_season_team(year=2013, team = "Florida State")
)
logos <- read.csv("https://raw.githubusercontent.com/sportsdataverse/cfbfastR-data/main/themes/logos.csv")
logos<- logos |> dplyr::select(-"conference")
df_team_season <- team_season_stats |>
   dplyr::left_join(logos, by=c("team"="school"))

df_team_season_long <- as.data.frame(t(as.matrix(df_team_season)))
colnames(df_team_season_long) <- df_team_season$team

Get Season Advanced Statistics by Team

df_team_season_adv <- dplyr::bind_rows(
   cfbd_stats_season_advanced(2019, team = "LSU"),
   cfbd_stats_season_advanced(2013, team = "Florida State")
)
df_team_season_adv <- df_team_season_adv |>
   dplyr::left_join(logos, by=c("team"="school"))

Get Game Advanced Stats

df_team_game_adv <- dplyr::bind_rows(
   cfbd_stats_game_advanced(2019, team = "LSU"),
   cfbd_stats_game_advanced(2013, team = "Florida State")
)
df_team_game_adv <- df_team_game_adv |>
   dplyr::left_join(logos, by=c("team"="school"))

Get Season Statistics by Player

source("https://raw.githubusercontent.com/sportsdataverse/cfbfastR-data/main/themes/gt_theme_code_SG.R")
passing_df <- dplyr::bind_rows(
   cfbd_stats_season_player(2019, team = "LSU", category = "passing"),
   cfbd_stats_season_player(2013, team = "Florida State", category = "passing")) |>
   dplyr::left_join(logos, by=c("team"="school")) |>
   dplyr::group_by(team) |>
   dplyr::mutate(logo = sprintf('<img src="%s" height="30" alt="%s logo">', logo, team)) |>
   dplyr::select(logo,
                 player,
                 passing_completions,
                 passing_att,
                 passing_yds,
                 passing_td,
                 passing_int,
                 passing_ypa) |>
   arrange( desc(passing_yds), team)

## Adding missing grouping variables: `team`

passing_df |> gt() |>
  tab_header(title = "Passing Summary") |>
  cols_label(logo="",
             player = "Player",
             passing_completions = "C",
             passing_att = "Att",
             passing_yds = "Yds",
             passing_td = "TDs",
             passing_int = "INTs",
             passing_ypa = "YPA") |>
  data_color(
    columns = c("passing_yds"),
    colors = scales::col_numeric(
      palette = "RdBu",
      domain = c(-6000,6000)
    )
  ) |>
  data_color(
    columns = c("passing_td"),
    colors = scales::col_numeric(
      palette = "RdBu",
      domain = c(-60,60)
    )
  ) |>
  data_color(
    columns = c("passing_td"),
    colors = scales::col_numeric(
      palette = "RdBu",
      domain = c(-60,60)
    )
  ) |>
  # Render the team logos from pre-built <img> HTML that carries alt text
  # (gt::web_image() cannot set alt; important for screen-reader accessibility).
  fmt_markdown(columns = "logo") |>
  tab_source_note(source_note = md("**Table:** @SaiemGilani | **Data:** @CFB_Data with @cfbfastR v2.0.0")) |>
  gt_theme_538(table.width = px(550))

## Warning: Since gt v0.9.0, the `colors` argument has been deprecated.
## • Please use the `fn` argument instead.
## This warning is displayed once every 8 hours.

	Player	C	Att	Yds	TDs	INTs	YPA
Passing Summary
LSU
	Joe Burrow	402	527	5671	60	6	10.8
	Myles Brennan	24	40	353	1	1	8.8
Florida State
	Jameis Winston	257	384	4057	40	10	10.6
	Jake Coker	18	36	250	0	1	6.9
	Sean Maguire	13	21	116	2	2	5.5
Table: @SaiemGilani \| Data: @CFB_Data with @cfbfastR v2.0.0

College Football Mapping for Stats Categories

cfbd_stats_categories()

## ── Stat categories for CollegeFootballData.com ─────────────── cfbfastR 3.0.0 ──

## ℹ Data updated: 2026-08-29 13:22:34 UTC

## # A tibble: 38 × 1
##    category          
##    <chr>             
##  1 completionAttempts
##  2 defensiveTDs      
##  3 extraPoints       
##  4 fieldGoalPct      
##  5 fieldGoals        
##  6 firstDowns        
##  7 fourthDownEff     
##  8 fumblesLost       
##  9 fumblesRecovered  
## 10 interceptions     
## # ℹ 28 more rows

Our Authors

Our Contributors

Citation

To cite the cfbfastR R package in publications, use:

BibTeX Citation

@misc{cfbfastr,
  author = {Saiem Gilani and Akshay Easwaran and Jared Lee and Eric Hess},
  title = {cfbfastR: Access College Football Play by Play Data},
  url = {https://cfbfastR.sportsdataverse.org/},
  year = {2021}
}

cfbfastR - college football
hoopR - men’s basketball
wehoop - women’s basketball
baseballr - baseball
fastRhockey - hockey
oddsapiR - betting odds
sportyR - playing surfaces
sportsdataverse-py - the Python package
sportsdataverse-R - the R meta-package

Saiem Gilani, Akshay Easwaran, Jared Lee

Load and Install Packages

Settling 2019 LSU and 2013 Florida State offense debates

Get Season Statistics by Team

Get Season Advanced Statistics by Team

Get Game Advanced Stats

Get Season Statistics by Player

College Football Mapping for Stats Categories

Our Authors

Our Contributors

Citation

Related SportsDataverse packages