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

Usage

bart_conf_factors(
  year = current_season(),
  conf = NULL,
  opp_conf = NULL,
  type = NULL,
  location = NULL,
  start = NULL,
  end = NULL
)

Arguments

year

Filters to year (YYYY)

conf

Filters to conference

opp_conf

Filters to opponent conference

type

Filters to game type ('nc', 'conf', or 'post')

location

Filters to game location ('H', 'A', or 'N')

start

Filters by starting date (YYYY-MM-DD)

end

Filters by ending date (YYYY-MM-DD)

Value

Returns a tibble with 21 columns:

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 possesion.

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. Data can be split on five variables:

venue

Splits on game location; 'all', 'home', 'away', 'neutral', and 'road' (away + neutral).

type

Splits on game type; 'all', 'nc' (non-conference), 'conf' (conference), 'reg' (regular season), 'post' (post-season tournaments), 'ncaa' (NCAA tournament).

quad

Splits by quadrant level; 1-4 with 0 indicating 1-A games.

top

Splits by opponent T-Rank position, adjusted for game location.

start/end

Splits by date range (YYYYMMDD).

Examples

bart_conf_factors(type='nc')
#> ── Conference Factors ────────────────────────────────────────── toRvik 1.0.2 ──
#>  Data updated: 2022-09-08 16:22:47 EDT
#> # A tibble: 32 × 21
#>    conf  rating  rank adj_o adj_o_r…¹ adj_d adj_d…² tempo off_ppp off_efg off_to
#>    <chr>  <dbl> <dbl> <dbl>     <dbl> <dbl>   <dbl> <dbl>   <dbl>   <dbl>  <dbl>
#>  1 B12    17.7      1  107.         3  89.0       1  68.7    109.    53.3   18.8
#>  2 B10    15.2      2  109.         1  94.1       3  69.0    110.    53.7   17.5
#>  3 SEC    13.8      3  106.         4  92.6       2  69.8    107.    50.8   18.2
#>  4 BE     12.2      4  107.         2  94.8       4  69.8    107.    51.8   18.3
#>  5 ACC    10.3      5  106.         5  96.0       7  68.4    107.    51.8   17.4
#>  6 P12    10.3      5  105.         6  95.2       6  69.2    106.    50.6   17.6
#>  7 Amer    8.88     6  104.         8  95.0       5  68.4    104.    50.3   18  
#>  8 MWC     7.6      7  104.         9  96.3       8  68.2    104.    51.7   17.9
#>  9 WCC     7.1      8  104.        10  96.7       9  68.8    103.    52.0   19.4
#> 10 A10     4.27     9  103.        11  98.8      10  68.4    104.    51.6   18.3
#> # … with 22 more rows, 10 more variables: 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
#> #   ¹​adj_o_rank, ²​adj_d_rank