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

## 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
# }
```