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Compute expected points

Source: R/ep_wp_calculators.R
calculate_expected_points.Rd

for provided plays. Returns the data with probabilities of each scoring event and EP added. The following columns must be present: season, home_team, posteam, roof (coded as 'open', 'closed', or 'retractable'), half_seconds_remaining, yardline_100, ydstogo, posteam_timeouts_remaining, defteam_timeouts_remaining

Usage

calculate_expected_points(pbp_data)

Arguments

pbp_data

Play-by-play dataset to estimate expected points for.

Value

The original pbp_data with the following columns appended to it:

ep

expected points.

no_score_prob

probability of no more scoring this half.

opp_fg_prob

probability next score opponent field goal this half.

opp_safety_prob

probability next score opponent safety this half.

opp_td_prob

probability of next score opponent touchdown this half.

fg_prob

probability next score field goal this half.

safety_prob

probability next score safety this half.

td_prob

probability text score touchdown this half.

Details

Computes expected points for provided plays. Returns the data with probabilities of each scoring event and EP added. The following columns must be present:

  • season

  • home_team

  • posteam

  • roof (coded as 'outdoors', 'dome', or 'open' / 'closed' / NA (retractable))

  • half_seconds_remaining

  • yardline_100

  • down

  • ydstogo

  • posteam_timeouts_remaining

  • defteam_timeouts_remaining

Examples

# \donttest{
library(dplyr)
data <- tibble::tibble(
"season" = 1999:2019,
"home_team" = "SEA",
"posteam" = "SEA",
"roof" = "outdoors",
"half_seconds_remaining" = 1800,
"yardline_100" = c(rep(80, 17), rep(75, 4)),
"down" = 1,
"ydstogo" = 10,
"posteam_timeouts_remaining" = 3,
"defteam_timeouts_remaining" = 3
)

nflfastR::calculate_expected_points(data) %>%
  dplyr::select(season, yardline_100, td_prob, ep)
#>    season yardline_100   td_prob        ep
#> 1    1999           80 0.3342112 0.6378878
#> 2    2000           80 0.3342112 0.6378878
#> 3    2001           80 0.3342112 0.6378878
#> 4    2002           80 0.3431796 0.8167660
#> 5    2003           80 0.3431796 0.8167660
#> 6    2004           80 0.3431796 0.8167660
#> 7    2005           80 0.3431796 0.8167660
#> 8    2006           80 0.3445111 0.8136176
#> 9    2007           80 0.3445111 0.8136176
#> 10   2008           80 0.3445111 0.8136176
#> 11   2009           80 0.3445111 0.8136176
#> 12   2010           80 0.3445111 0.8136176
#> 13   2011           80 0.3445111 0.8136176
#> 14   2012           80 0.3445111 0.8136176
#> 15   2013           80 0.3445111 0.8136176
#> 16   2014           80 0.3522740 0.9822985
#> 17   2015           80 0.3522740 0.9822985
#> 18   2016           75 0.3771672 1.4573911
#> 19   2017           75 0.3771672 1.4573911
#> 20   2018           75 0.4067504 1.4740978
#> 21   2019           75 0.4067504 1.4740978
# }