Quick question: scoring/code

[jacobakaye]

Hi. How do I make sure my code has PPR scoring in it? And also, how can I interpret the "add_risk" variable? Thanks! Here's my code:

library(ffanalytics)
library(tidyverse)
library(dplyr)
library(tidyr)

my_scrape <- scrape_data(src = c("CBS", "NFL", "ESPN", "NumberFire"), 
                         pos = c("QB", "RB", "WR", "TE", "DST"),
                         season = NULL, # NULL grabs the current season
                         week = NULL) # NULL grabs the current week

my_projections <-  projections_table(my_scrape)

my_projections <- my_projections %>% 
  add_ecr() %>% 
  add_adp() %>% 
  add_aav() %>%
  add_uncertainty()

my_projections <- my_projections %>% 
  add_player_info()

view(my_projections)

[atungate]

Hey Jacob, you'll want to create your own scoring object, make sure receptions are 1pt, and then pass that to the projections table function. Like so:

# Create a scoring object using our default scoring object
scoring_obj = ffanalytics::scoring

# Look at receptions
scoring_obj$rec$rec

# Set receptions to be equal to 1 point
scoring_obj$rec$rec = 1

# Use scoring object 
my_projections = projections_table(my_scrape, scoring_rules = scoring_obj)

Let us know if you have any other questions!

[jacobakaye]

Hi. Thank you. Would I have to change all the scoring categories to PPR?

[jacobakaye]

Also, are all the functions working? Could you possibly provide more sample code on the website to calculate projections?

[atungate]

Hey Jacob, you would have to update any part of the scoring object that is not in-line with your league settings. E.g., if your league gives 5 points for passing touchdowns you would want to make sure your scoring settings reflect that. I.e.:

scoring_obj$pass$pass_tds = 5

You then pass the scoring object to your projections table function.

As for your second question--"are all the functions working?" I'll need you to be a bit more specific. What are you confused about?

[atungate]

Ah, I just saw you asked about theadd_risk() function as well. We no longer export it / it is superseded by theadd_uncertainty() function.

[jacobakaye]

How can I use these functions:

confidence_interval() set_tiers()

I'm just trying to learn how to use this package. Thanks!

[jacobakaye]

I would like these settings for the scoring, but I'm not sure how to exactly make sure it's set within the code:

list(
  pass = list(
    pass_att = 0, pass_comp = 0, pass_inc = 0, pass_yds = 0.04, pass_tds = 4,
    pass_int = -2, pass_40_yds = 0,  pass_300_yds = 0, pass_350_yds = 0,
    pass_400_yds = 0
  ),
  rush = list(
    all_pos = TRUE,
    rush_yds = 0.1,  rush_att = 0, rush_40_yds = 0, rush_tds = 6,
    rush_100_yds = 0, rush_150_yds = 0, rush_200_yds = 0),
  rec = list(
    all_pos = TRUE,
    rec = 1, rec_yds = 0.1, rec_tds = 6, rec_40_yds = 0, rec_100_yds = 0,
    rec_150_yds = 0, rec_200_yds = 0
  ),
  misc = list(
    all_pos = TRUE,
    fumbles_lost = -2, fumbles_total = 0,
    sacks = 0, two_pts = 2
  ),
  kick = list(
    xp = 1.0, fg_0019 = 3.0,  fg_2029 = 3.0, fg_3039 = 3.0, fg_4049 = 4.0,
    fg_50 = 5.0,  fg_miss = 0.0
  ),
  ret = list(
    all_pos = TRUE,
    return_tds = 6, return_yds = 0
  ),
  dst = list(
    dst_fum_rec = 2,  dst_int = 2, dst_safety = 2, dst_sacks = 1, dst_td = 6,
    dst_blk = 1.5, dst_ret_yds = 0, dst_pts_allowed = 0
  ),
  pts_bracket = list(
    list(threshold = 0, points = 10),
    list(threshold = 6, points = 7),
    list(threshold = 20, points = 4),
    list(threshold = 34, points = 0),
    list(threshold = 99, points = -4)
  )
)

[atungate]

Hey Jacob, you shouldn't use the confidence_interval() or set_tiers() functions / they are not exported. Also, you would assign that list to object (my_scoring = list(you_list_from_above)) and pass it as the scoring object to the projections_table() function. Let me know if sample code would be helpful but I am going to close this for now (feel free to reply still if you are still having issues)

[jacobakaye]

Hi. Yes, please. Also, any other code to prepare for a 12-team PPR draft would be awesome if you can!

[jacobakaye]

I think something is wrong here... could you possibly help me out?

library(ffanalytics)
library(tidyverse)
library(dplyr)
library(tidyr)
library(dplyr)

my_scrape <- scrape_data(src = c("CBS", "NFL", "ESPN", "NumberFire"), 
                         pos = c("QB", "RB", "WR", "TE", "DST"),
                         season = NULL, # NULL grabs the current season
                         week = NULL) # NULL grabs the current week

my_projections <-  projections_table(my_scrape)

my_projections <- my_projections %>% 
  add_ecr() %>% 
  add_adp() %>% 
  add_aav() %>%
  add_uncertainty()

# Create a scoring object using our default scoring object
scoring_obj = list(
  pass = list(
    pass_att = 0, pass_comp = 0, pass_inc = 0, pass_yds = 0.04, pass_tds = 4,
    pass_int = -2, pass_40_yds = 0,  pass_300_yds = 0, pass_350_yds = 0,
    pass_400_yds = 0
  ),
  rush = list(
    all_pos = TRUE,
    rush_yds = 0.1,  rush_att = 0, rush_40_yds = 0, rush_tds = 6,
    rush_100_yds = 0, rush_150_yds = 0, rush_200_yds = 0),
  rec = list(
    all_pos = TRUE,
    rec = 1, rec_yds = 0.1, rec_tds = 6, rec_40_yds = 0, rec_100_yds = 0,
    rec_150_yds = 0, rec_200_yds = 0
  ),
  misc = list(
    all_pos = TRUE,
    fumbles_lost = -2, fumbles_total = 0,
    sacks = 0, two_pts = 2
  ),
  kick = list(
    xp = 1.0, fg_0019 = 3.0,  fg_2029 = 3.0, fg_3039 = 3.0, fg_4049 = 4.0,
    fg_50 = 5.0,  fg_miss = 0.0
  ),
  ret = list(
    all_pos = TRUE,
    return_tds = 6, return_yds = 0
  ),
  dst = list(
    dst_fum_rec = 2,  dst_int = 2, dst_safety = 2, dst_sacks = 1, dst_td = 6,
    dst_blk = 1.5, dst_ret_yds = 0, dst_pts_allowed = 0
  ),
  pts_bracket = list(
    list(threshold = 0, points = 10),
    list(threshold = 6, points = 7),
    list(threshold = 20, points = 4),
    list(threshold = 34, points = 0),
    list(threshold = 99, points = -4)
  )
)

# Look at receptions
scoring_obj$rec$rec

# Set receptions to be equal to 1 point
scoring_obj$rec$rec = 1

# Use scoring object 
my_projections = projections_table(my_scrape, scoring_rules = scoring_obj)

my_projections

my_projections <- my_projections %>% 
  add_player_info()

view(my_projections)

# Filter for each position separately
qb_projections <- my_projections %>%
  filter(pos == "QB")

rb_projections <- my_projections %>%
  filter(pos == "RB")

wr_projections <- my_projections %>%
  filter(pos == "WR")

te_projections <- my_projections %>%
  filter(pos == "TE")

# View each position-specific data frame
View(qb_projections)
View(rb_projections)
View(wr_projections)
View(te_projections)

#?add_adp
#?add_aav

view(my_projections)