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

calculate_expected_points(pbp_data)

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

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

# \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# }