Get Four Factor Statistics — bart

Returns four factor data and team records on a variety of splits, including date range, quadrant level, opponent ranking, game location, and game type.

Usage

bart_factors(
  year = current_season(),
  result = NULL,
  type = NULL,
  start = NULL,
  end = NULL,
  location = NULL,
  last = NULL
)

Arguments

year: Defaults to current season (YYYY).
result: Filters by result ('W' or 'L')
type: Filter by game type ('nc', 'conf', or 'post')
start: Filters by starting date (YYYY-MM-DD)
end: Filters by ending date (YYYY-MM-DD)
location: Filters by game location ('H', 'A', or 'N')
last: Filters by last x games played

Value

Returns a tibble with 22 columns:

team: character.
conf: character.
rating: double. Expected scoring margin against an average team on a neutral court.
rank: double.
adj_o: double.
adj_o_rank: double.
adj_d: double.
adj_d_rank: double.
tempo: double.
off_ppp: double. Raw points scored per possession.
off_efg: double. Team effective FG%.
off_to: double. Offensive turnover rate.
off_or: double. Offensive rebound rate.
off_ftr: double. Offensive free throw rate.
def_ppp: double. Raw points allowed per possession.
def_efg: double. Effective FG% allowed.
def_to: double. Turnover rate forced.
def_or: double. Defensive rebound rate.
def_ftr: double. Free throw rate allowed.
wins: integer.
losses: integer.
games: integer.

Details

For a brief explanation of each factor and its computation, please visit KenPom's blog.

Examples

bart_factors(year=2022, start='2022-01-13', type='conf')
#> ── Team Factors ──────────────────────────────────────────────── toRvik 1.1.0 ──
#> ℹ Data updated: 2022-09-20 01:38:52 UTC
#> # A tibble: 358 × 22
#>    team     conf  rating  rank adj_o adj_o…¹ adj_d adj_d…² tempo off_ppp off_efg
#>    <chr>    <chr>  <dbl> <dbl> <dbl>   <dbl> <dbl>   <dbl> <dbl>   <dbl>   <dbl>
#>  1 Gonzaga  WCC     32.1     1  120.       5  87.7       3  74.9    118.    59.6
#>  2 Duke     ACC     28.6     2  123.       1  94.4      39  66.1    117.    56.4
#>  3 Kansas   B12     27.2     3  120.       4  92.8      21  68.6    109.    52.5
#>  4 Houston  Amer    26.1     4  114.      22  88.4       6  65.5    110.    52.5
#>  5 Kentucky SEC     25.6     5  122.       3  96.6      63  68.4    113.    53.0
#>  6 Baylor   B12     25.3     6  117.      13  91.3      12  67.0    106.    50.2
#>  7 Arizona  P12     24.8     7  118.       9  92.8      19  71.7    113.    55.5
#>  8 Iowa     B10     24.6     8  119.       7  94.2      36  69.2    114.    51.2
#>  9 Purdue   B10     24.2     9  122.       2  98.1      84  65.9    115.    56.1
#> 10 Villano… BE      23.8    10  120.       6  96.0      56  65.5    115.    55.2
#> # … with 348 more rows, 11 more variables: off_to <dbl>, off_or <dbl>,
#> #   off_ftr <dbl>, def_ppp <dbl>, def_efg <dbl>, def_to <dbl>, def_or <dbl>,
#> #   def_ftr <dbl>, wins <int>, losses <int>, games <int>, and abbreviated
#> #   variable names ¹adj_o_rank, ²adj_d_rank