Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
options(dplyr.summarise.inform = FALSE,
rmarkdown.html_vignette.check_title = FALSE)
eval <- TRUE
tryCatch(expr = {
download.file("https://github.com/ffverse/ffscrapr-tests/archive/1.4.7.zip","f.zip")
unzip('f.zip', exdir = ".")
httptest::.mockPaths(new = "ffscrapr-tests-1.4.7")},
warning = function(e) eval <<- FALSE,
error = function(e) eval <<- FALSE)
httptest::use_mock_api()
## ----setup, message=FALSE, eval = eval----------------------------------------
library(ffscrapr)
library(dplyr)
library(tidyr)
## ----eval = eval--------------------------------------------------------------
aaa <- fleaflicker_connect(season = 2020, league_id = 312861)
aaa
## ----eval = eval--------------------------------------------------------------
aaa_summary <- ff_league(aaa)
str(aaa_summary)
## ----eval = eval--------------------------------------------------------------
aaa_rosters <- ff_rosters(aaa)
head(aaa_rosters)
## ----eval = eval--------------------------------------------------------------
player_values <- dp_values("values-players.csv")
# The values are stored by fantasypros ID since that's where the data comes from.
# To join it to our rosters, we'll need playerID mappings.
player_ids <- dp_playerids() %>%
select(sportradar_id,fantasypros_id) %>%
filter(!is.na(sportradar_id),!is.na(fantasypros_id))
# We'll be joining it onto rosters, so we can trim down the values dataframe
# to just IDs, age, and values
player_values <- player_values %>%
left_join(player_ids, by = c("fp_id" = "fantasypros_id")) %>%
select(sportradar_id,age,ecr_2qb,ecr_pos,value_2qb)
# ff_rosters() will return the sportradar_id, which we can then match to our player values!
aaa_values <- aaa_rosters %>%
left_join(player_values, by = c("sportradar_id"="sportradar_id")) %>%
arrange(franchise_id,desc(value_2qb))
head(aaa_values)
## ----eval = eval--------------------------------------------------------------
value_summary <- aaa_values %>%
group_by(franchise_id,franchise_name,pos) %>%
summarise(total_value = sum(value_2qb,na.rm = TRUE)) %>%
ungroup() %>%
group_by(franchise_id,franchise_name) %>%
mutate(team_value = sum(total_value)) %>%
ungroup() %>%
pivot_wider(names_from = pos, values_from = total_value) %>%
arrange(desc(team_value)) %>%
select(franchise_id,franchise_name,team_value,QB,RB,WR,TE)
value_summary
## ----eval = eval--------------------------------------------------------------
value_summary_pct <- value_summary %>%
mutate_at(c("team_value","QB","RB","WR","TE"),~.x/sum(.x)) %>%
mutate_at(c("team_value","QB","RB","WR","TE"),round, 3)
value_summary_pct
## ----eval = eval--------------------------------------------------------------
age_summary <- aaa_values %>%
filter(pos %in% c("QB","RB","WR","TE")) %>%
group_by(franchise_id,pos) %>%
mutate(position_value = sum(value_2qb,na.rm=TRUE)) %>%
ungroup() %>%
mutate(weighted_age = age*value_2qb/position_value,
weighted_age = round(weighted_age, 1)) %>%
group_by(franchise_id,franchise_name,pos) %>%
summarise(count = n(),
age = sum(weighted_age,na.rm = TRUE)) %>%
pivot_wider(names_from = pos,
values_from = c(age,count))
age_summary
## ----include = FALSE----------------------------------------------------------
httptest::stop_mocking()
unlink(c("ffscrapr-tests-1.4.7","f.zip"), recursive = TRUE, force = TRUE)
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