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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
# toRvik <a href="https://www.torvik.dev/"><img src="man/figures/logo.png" align="right" width="20%" min-width="100px"/></a>
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[](https://CRAN.R-project.org/package=toRvik) [](https://lifecycle.r-lib.org/articles/stages.html#stable) [](https://github.com/andreweatherman/toRvik/actions) [](https://app.codecov.io/gh/andreweatherman/toRvik?branch=main)
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[**`toRvik`**](https://github.com/andreweatherman/toRvik) is an R package for working with and scraping men's college basketball.
There are a lot of college basketball data out there, but most are difficult to pull and clean or they are behind a paywall. With `toRvik`, you have immediate access to some of the most detailed and extensive college basketball statistics publicly available -- all returned in tidy format with just a single line of code! Best of all, no subscription is required to access the data.\
\
Most of `toRvik`'s functions are powered by a dedicated Fast API framework -- delivering data at rapid speeds with dependable up-times.
As of version 1.0.3, the package includes nearly 30 functions for pulling player and team data, game results, advanced metric splits, play-by-play shooting, and more. Leveraging the same data and models as [Barttorvik](https://www.barttorvik.com), the package now offers game and tournament predictor functions, allowing you to simulate games between any pair of teams on any date at any venue back to the 2014-15 season. `toRvik` also offers extensive transfer histories for over 5,000 players back to the 2011-12 season and detailed player recruiting rankings for over 6,000 players back to 2007-08.
## Package Installation
```{r, include=FALSE}
library(dplyr)
library(toRvik)
```
Install the released version of `toRvik` from CRAN:
```{r, eval=FALSE}
install.packages("toRvik")
```
Or install the development version from GitHub with:
```{r, eval=FALSE}
if (!requireNamespace('devtools', quietly = TRUE)){
install.packages('devtools')
}
devtools::install_github("andreweatherman/toRvik")
```
## Package Highlights
- Detailed game-by-game + season-long statistics by player and split
- Extensive transfer + recruiting histories
- Custom game and tournament predictions
- Shooting splits + shares by team
- Game box scores for all D-1 games
- Team + conference four factors by split
- Game-by-game four factors
- NCAA committee-style team sheets
- D-1 head coaching changes
## Basic Uses
All `toRvik` functions fall into one of six categories:
- **Rating**, pulling and slicing T-Rank + four factor data
- **Player**, pulling player data and histories
- **Team**, pulling team statistics and histories
- **Game**, pulling game-by-game data and schedules
- **Tournament**, pulling raw and adjusted tournament performance
- **Miscellaneous**
### Pull T-Rank ratings:
Calling `bart_ratings` will return the current T-Rank ranks and ratings.
```{r}
head(bart_ratings())
```
### Pull team statistics
Calling `bart_factors` will return four factor stats on a number of splits. To filter by home games, set venue to 'home.'
```{r}
head(bart_factors(location='H'))
```
Calling `bart_team_box` will return team box totals and per-game averages by game type. To find how Duke performed during the month of March:
```{r}
bart_team_box(team='Duke', split='month') |>
dplyr::filter(month=='March')
```
### Pull player statistics
Calling `bart_player_season` will return detailed season-long player stats. To pull per-game averages for Duke players:
```{r}
head(bart_player_season(team='Duke', stat='box'))
```
Calling `bart_player_game` will return detailed game-by-game player stats. To pull advance splits by game for Duke players:
```{r}
head(bart_player_game(team='Duke', stat='advanced'))
```
### Pull transfer histories
Calling `transfer_portal` will return transfer histories with matching player IDs to join with other statistics. To find all players who transferred to Duke:
```{r}
head(transfer_portal(to='Duke'))
```
### Pull recruiting rankings
Calling `player_recruiting_rankings` will return extensive recruit histories with matching player IDs. To find all 5-star players who played high school basketball in North Carolina:
```{r}
head(player_recruiting_rankings(stars=5, state='NC'))
```
### Predict games and tournaments
Calling `bart_game_predictions` will returns expected points, possessions, and win percentage for a given game on a given date. To simulate North Carolina at Duke in mid-January:
```{r}
bart_game_prediction('Duke', 'North Carolina', '20220113', location = 'H')
```
Calling `bart_tournament_prediction` will simulate a single-elimination tournament between a group of teams on a given date. To simulate the 2022 Final Four 25 times:
```{r}
bart_tournament_prediction(teams = c('Duke', 'North Carolina', 'Kansas', 'Villanova'), '20220402', sims = 25, seed = 10)
```
## Documentation
For more information on the package and its functions, please see the [**`toRvik`** reference](https://www.torvik.dev/).
## The Author
[Andrew Weatherman](https://www.linkedin.com/in/andrewweatherman/)
<a href="https://twitter.com/andreweatherman" target="blank"><img src="https://img.shields.io/twitter/follow/andreweatherman?color=blue&label=%40andreweatherman&logo=twitter&style=for-the-badge" alt="@andreweatherman"/></a>