Type: | Package |
Title: | Professional Sports Draft Data |
Version: | 1.0.3 |
Author: | Benjamin Ginsburg [aut, cre] |
Maintainer: | Benjamin Ginsburg <benjamin.ginsburg@du.edu> |
Description: | We provide comprehensive draft data for major professional sports leagues, including the National Football League (NFL), National Basketball Association (NBA), and National Hockey League (NHL). It offers access to both historical and current draft data, allowing for detailed analysis and research on player biases and player performance. The package is useful for sports fans and researchers interested in identifying biases and trends within scouting reports. Created by web scraping data from leading websites that cover professional sports player scouting reports, the package allows users to filter and summarize data for analytical purposes. For further details on the methods used, please refer to Wickham (2022) "rvest: Easily Harvest (Scrape) Web Pages" https://CRAN.R-project.org/package=rvest and Harrison (2023) "RSelenium: R Bindings for Selenium WebDriver" https://CRAN.R-project.org/package=RSelenium. |
Encoding: | UTF-8 |
LazyData: | true |
RoxygenNote: | 7.3.2 |
URL: | https://github.com/Ginsburg1/ProSportsDraftData |
BugReports: | https://github.com/Ginsburg1/ProSportsDraftData/issues |
Imports: | dplyr, stats |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Config/testthat/edition: | 3 |
Depends: | R (≥ 3.5.0) |
VignetteBuilder: | knitr |
License: | GPL-3 |
NeedsCompilation: | no |
Packaged: | 2024-08-28 22:16:16 UTC; benjaminginsburg |
Repository: | CRAN |
Date/Publication: | 2024-09-03 14:30:08 UTC |
ProSportsDraftData: Professional Sports Draft Data
Description
The 'ProSportsDraftData' package provides comprehensive draft data for major professional sports leagues, including the National Football League (NFL), National Basketball Association (NBA), and National Hockey League (NHL). It offers access to both historical and current draft data, allowing for detailed analysis and research on player biases and player performance. The package is useful for sports fans and researchers interested in identifying biases and trends within scouting reports. Created by web scraping data from leading websites that cover professional sports player scouting reports, the package allows users to filter and summarize data for analytical purposes. For further details on the methods used, please refer to Wickham (2022) "rvest: Easily Harvest (Scrape) Web Pages" https://CRAN.R-project.org/package=rvest and Harrison (2023) "RSelenium: R Bindings for Selenium WebDriver" https://CRAN.R-project.org/package=RSelenium.
Author(s)
Maintainer: Benjamin Ginsburg benjamin.ginsburg@du.edu
See Also
Useful links:
Report bugs at https://github.com/Ginsburg1/ProSportsDraftData/issues
NBA Draft Data
Description
A dataset of all first-round picks in the NBA, including various draft metrics.
Usage
nba_data
Format
A tibble
with the following columns:
source
The source of the data.
name
The name of the player.
year
The year of the draft.
rank
The rank of the player in the draft.
round
The round in which the player was drafted.
height
The height of the player.
weight
The weight of the player.
school
The school the player attended.
college_abbreviation
The abbreviation of the college the player attended.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
verdict
The overall verdict on the player's potential.
pre_draft_analysis
Analysis of the player before the draft.
post_draft_analysis
Analysis of the player after the draft.
ranking
The player's ranking.
player_score
The score given to the player.
position
The position the player plays.
grade
The grade given to the player.
pts_total
Total points scored by the player.
pts_per40
Points per 40 minutes played.
reb_total
Total rebounds by the player.
reb_per40
Rebounds per 40 minutes played.
ast_total
Total assists by the player.
ast_per40
Assists per 40 minutes played.
efg
Effective field goal percentage.
fga
Field goal attempts.
stl_total
Total steals by the player.
stl_per40
Steals per 40 minutes played.
blk_total
Total blocks by the player.
blk_per40
Blocks per 40 minutes played.
tpt
Three-point shots made.
tpa
Three-point attempts.
ft
Free throws made.
fta
Free throw attempts.
ts
True shooting percentage.
ts_att
True shooting attempts.
main_selling_point
The main selling point of the player.
age
The age of the player at the time of the draft.
wingspan
The wingspan of the player.
standing_reach
The standing reach of the player.
similar_player
A player with a similar profile.
profile
Profile description of the player.
analysis
An analysis of the player's potential and performance.
projection
Projection of the player's future performance.
date_of_birth
The date of birth of the player.
hometown
The hometown of the player.
high_school
The high school the player attended.
rebounding
Evaluation of the player's rebounding skills.
potential
Evaluation of the player's potential.
post_skills
Evaluation of the player's post skills.
intangibles
Evaluation of the player's intangibles.
international_team
The international team the player has been part of.
athleticism
Evaluation of the player's athleticism.
size
Evaluation of the player's size.
defense
Evaluation of the player's defensive skills.
strength
Evaluation of the player's strength.
quickness
Evaluation of the player's quickness.
leadership
Evaluation of the player's leadership skills.
jumpshot
Evaluation of the player's jumpshot.
nba_ready
Evaluation of the player's NBA readiness.
mock_draft_rank
The player's ranking in mock drafts.
big_board_rank
The player's ranking on big boards.
overall_rank
The player's overall ranking.
Examples
# Load the dataset
data(nba_data)
# View the first few rows
head(nba_data)
# View players who attended Duke
library(dplyr)
duke_players <- nba_data |>
filter(college_abbreviation == "DUKE")
print(duke_players)
# Average score by position
avg_score_by_position <- nba_data |>
group_by(position) |>
summarise(avg_score = mean(player_score, na.rm = TRUE))
print(avg_score_by_position)
# Calculate the average points per 40 minutes
avg_pts_per40 <- nba_data |>
summarise(avg_pts = mean(pts_per40, na.rm = TRUE))
print(avg_pts_per40)
# Count the number of players from each college
college_counts <- nba_data |>
group_by(college_abbreviation) |>
summarise(count = n())
print(college_counts)
NBA Data Base
Description
Filter NBA Data by Source (Base)
Usage
nba_data_base()
Format
A tibble
with the following columns:
name
The name of the player.
year
The year of the draft.
round
The round in which the player was drafted.
Details
Filters and selects NBA data from the Base (ESPN.com) source.
Value
A filtered and selected tibble of NBA data from Base.
Examples
# Filter NBA data for base source
base_data <- nba_data_base()
# View the first few rows
head(base_data)
NBA Data ESPN
Description
Filter NBA Data by Source (ESPN)
Usage
nba_data_espn()
Format
A tibble
with the following columns:
name
The name of the player.
year
The year of the draft.
height
The height of the player.
weight
The weight of the player.
school
The school the player attended.
college_abbreviation
The abbreviation of the college the player attended.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
verdict
The overall verdict on the player's potential.
pre_draft_analysis
Analysis of the player before the draft.
post_draft_analysis
Analysis of the player after the draft.
ranking
The player's ranking.
player_score
The score given to the player.
Details
Filters and selects NBA data from ESPN for the given source value.
Value
A filtered and selected tibble of NBA data from ESPN.
Examples
# Filter NBA data for ESPN
espn_data <- nba_data_espn()
# View the first few rows
head(espn_data)
NBA Data NBA.com
Description
Filter NBA Data by Source (NBA.com)
Usage
nba_data_nba_com()
Format
A tibble
with the following columns:
name
The name of the player.
year
The year of the draft.
position
The position the player plays.
school
The school the player attended.
weight
The weight of the player.
grade
The grade given to the player.
date_of_birth
The date of birth of the player.
profile
Profile description of the player.
analysis
An analysis of the player's potential and performance.
projection
Projection of the player's future performance.
Details
Filters and selects NBA data from NBA.com for the given source value.
Value
A filtered and selected tibble of NBA data from NBA.com.
Examples
# Filter NFL data for NBA.com
nba_com <- nba_data_nba_com()
# View the first few rows
head(nba_com)
NBA Data NBADraft.net
Description
Filter NBA Data by Source (NBADraft.net)
Usage
nba_data_nbadraft_net()
Format
A tibble
with the following columns:
name
The name of the player.
height
The height of the player.
weight
The weight of the player.
position
The position the player plays.
school
The school the player attended.
date_of_birth
The date of birth of the player.
hometown
The hometown of the player.
high_school
The high school the player attended.
international_team
The international team the player has been part of.
athleticism
Evaluation of the player's athleticism.
size
Evaluation of the player's size.
defense
Evaluation of the player's defensive skills.
strength
Evaluation of the player's strength.
quickness
Evaluation of the player's quickness.
leadership
Evaluation of the player's leadership skills.
jumpshot
Evaluation of the player's jumpshot.
nba_ready
Evaluation of the player's NBA readiness.
rebounding
Evaluation of the player's rebounding skills.
potential
Evaluation of the player's potential.
post_skills
Evaluation of the player's post skills.
intangibles
Evaluation of the player's intangibles.
mock_draft_rank
The player's ranking in mock drafts.
big_board_rank
The player's ranking on big boards.
overall_rank
The player's overall ranking.
similar_player
A player with a similar profile.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
Details
Filters and selects NBA data from NBADraft.net for the given source value.
Value
A filtered and selected tibble of NBA data from NBADraft.net.
Examples
# Filter NFL data for NBADraft.net
nbadraft <- nba_data_nbadraft_net()
# View the first few rows
head(nbadraft)
NBA Data The Ringer
Description
Filter NBA Data by Source (The Ringer)
Usage
nba_data_the_ringer()
Format
A tibble
with the following columns:
name
The name of the player.
year
The year of the draft.
position
The position the player plays.
school
The school the player attended.
grade
The grade given to the player.
pts_total
Total points scored by the player.
pts_per40
Points per 40 minutes played.
reb_total
Total rebounds by the player.
reb_per40
Rebounds per 40 minutes played.
ast_total
Total assists by the player.
ast_per40
Assists per 40 minutes played.
efg
Effective field goal percentage.
fga
Field goal attempts.
stl_total
Total steals by the player.
stl_per40
Steals per 40 minutes played.
blk_total
Total blocks by the player.
blk_per40
Blocks per 40 minutes played.
tpt
Three-point shots made.
tpa
Three-point attempts.
ft
Free throws made.
fta
Free throw attempts.
ts
True shooting percentage.
ts_att
True shooting attempts.
main_selling_point
The main selling point of the player.
age
The age of the player at the time of the draft.
height
The height of the player.
weight
The weight of the player.
wingspan
The wingspan of the player.
standing_reach
The standing reach of the player.
analysis
An analysis of the player's potential and performance.
similar_player
A player with a similar profile.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
Details
Filters and selects NBA data from The Ringer for the given source value.
Value
A filtered and selected tibble of NBA data from The Ringer.
Examples
# Filter NFL data for The Ringer
ringer_data <- nba_data_the_ringer()
# View the first few rows
head(ringer_data)
NFL Draft Data
Description
A dataset of all first-round picks in the NFL, including various draft metrics.
Usage
nfl_data
Format
A tibble
with the following columns:
source
The source of the data.
name
The name of the player.
year
The year of the draft.
rank
The rank of the player.
round
The round in which the player was drafted.
height
The height of the player.
weight
The weight of the player.
position
The position of the player.
college
The college the player attended.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
similar_player
A similar player for comparison.
summary
A summary of the player's abilities.
arm_length
The arm length of the player.
hand_length
The hand length of the player.
next_gen_production_score
The Next Gen production score.
next_gen_athleticism_score
The Next Gen athleticism score.
forty_yard_dash
The forty-yard dash time.
vertical_jump
The vertical jump height.
nfl_prospect_grade
The NFL prospect grade.
home_town
The hometown of the player.
broad_jump
The broad jump distance.
three_cone_drill
The three-cone drill time.
twenty_yard_shuttle
The twenty-yard shuttle time.
bench_press
The bench press reps.
college_abbrivation
The abbreviation of the college.
pre_draft
Pre-draft information.
post_draft
Post-draft information.
position_rank
The position rank of the player.
overall_rank
The overall rank of the player.
grade
The grade of the player.
school
The school the player attended.
yds
Yards the player ran.
ypa
The yards per attempt.
ypr
The yards per reception.
tds
Number of touchdowns the player performed.
ints
The interceptions.
rtg
The rating of the player.
tkls
The number of taclees of the player.
tfl
The tackles for loss.
ypc
The yards per carry.
pbu
The pass break-ups of the player.
twenty_plus
Plays of twenty or more yards.
sacks
Number of sacks of the player.
gms
The number of games played.
strts
The number of games started.
sk_all
The number of sack allowed.
age
The age of the player.
main_selling_point
The main selling point of the player.
description
The description of the player.
scouting_report
The scouting report.
score
Players score from 1-100.
Examples
# Load the dataset
data(nfl_data)
# View the first few rows
head(nfl_data)
# Filter data for NFL.com source
nfl_com_data <- nfl_data[nfl_data$source == "NFL.com", ]
# Filter data for The Ringer source
the_ringer_data <- nfl_data[nfl_data$source == "The Ringer", ]
NFL Data Base
Description
Filter NFL Data by Source (Base)
Usage
nfl_data_base()
Format
A tibble
with the following columns:
name
The name of the player.
round
The round in which the player was drafted.
rank
The rank of the player.
Details
Filters and selects NFL data from the base source for the given source value.
Value
A filtered and selected tibble of NFL data.
Examples
# Filter NFL data for base source
base_data <- nfl_data_base()
# View the first few rows
head(base_data)
NFL Data ESPN
Description
Filter NFL Data by Source (ESPN)
Usage
nfl_data_espn()
Format
A tibble
with the following columns:
source
The source of the data.
name
The name of the player.
year
The year of the draft.
height
The height of the player.
weight
The weight of the player.
college
The college the player attended.
college_abbrivation
The abbreviation of the college.
pre_draft
Pre-draft information.
post_draft
Post-draft information.
position_rank
The position rank of the player.
overall_rank
The overall rank of the player.
score
The player's score from 1-100.
Details
Filters and selects NFL data from ESPN for the given source value.
Value
A filtered and selected tibble of NFL data from ESPN.
Examples
# Filter NFL data for ESPN source
espn_data <- nfl_data_espn()
# View the first few rows
head(espn_data)
NFL Data NFL.com
Description
Filter NFL Data by Source (NFL.com)
Usage
nfl_data_nfl_com()
Format
A tibble
with the following columns:
name
The name of the player.
year
The draft year of the player.
height
The height of the player.
weight
The weight of the player.
position
The position of the player.
college
The college the player attended.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
similar_player
A similar player for comparison.
summary
A summary of the player's abilities.
Details
Filters and selects NFL data from NFL.com for the given source value.
Value
A filtered and selected tibble of NFL data from NFL.com.
Examples
# Filter NFL data for NFL.com
nfl_data <- nfl_data_nfl_com()
# View the first few rows
head(nfl_data)
NFL Data The Ringer
Description
Filter NFL Data by Source (The Ringer)
Usage
nfl_data_the_ringer()
Format
A tibble
with the following columns:
name
The name of the player.
rank
The rank of the player.
year
The draft year of the player.
position
The position of the player.
college
The college the player attended.
grade
The grade of the player.
yds
The number of yards the player ran.
ypa
The yards per attempt.
ypr
The yards per reception.
tds
The number of touchdowns by the player.
ints
The number of interceptions.
rtg
The rating of the player.
tkls
The number of tackles by the player.
tfl
The number of tackles for loss.
ypc
The yards per carry.
pbu
The number of pass break-ups by the player.
twenty_plus
The number of plays of twenty or more yards.
sacks
The number of sacks by the player.
gms
The number of games played.
strts
The number of games started.
sk_all
The number of sacks allowed by the player.
height
The height of the player.
weight
The weight of the player.
age
The age of the player.
main_selling_point
The main selling point of the player.
description
A description of the player.
similar_player
A similar player for comparison.
scouting_report
The scouting report of the player.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
Details
Filters and selects NFL data from The Ringer for the given source value.
Value
A filtered and selected tibble of NFL data from The Ringer.
Examples
# Filter NFL data for The Ringer
ringer_data <- nfl_data_the_ringer()
# View the first few rows
head(ringer_data)
NFL Data Walter Football
Description
Filter NFL Data by Source (Walter Football)
Usage
nfl_data_walter_football()
Format
A tibble
with the following columns:
name
The name of the player.
year
The draft year of the player.
height
The height of the player.
weight
The weight of the player.
arm_length
The arm length of the player.
hand_length
The hand length of the player.
college
The college the player attended.
position
The position of the player.
next_gen_production_score
The Next Gen production score.
next_gen_athleticism_score
The Next Gen athleticism score.
forty_yard_dash
The forty-yard dash time.
vertical_jump
The vertical jump height.
nfl_prospect_grade
The NFL prospect grade.
home_town
The hometown of the player.
broad_jump
The broad jump distance.
three_cone_drill
The three-cone drill time.
twenty_yard_shuttle
The twenty-yard shuttle time.
bench_press
The bench press reps.
similar_player
A similar player for comparison.
summary
A summary of the player's abilities.
pros
The pros of the player's abilities.
cons
The cons of the player's abilities.
Details
Filters and selects NFL data from Walter Football for the given source value.
Value
A filtered and selected tibble of NFL data from Walter Football.
Examples
# Filter NFL data for Walter Football source
walter_data <- nfl_data_walter_football()
# View the first few rows
head(walter_data)
NHL Draft Data
Description
A dataset of all first-round picks in the NHL, including various draft metrics.
Usage
nhl_data
Format
A tibble
with the following columns:
source
The source of the data.
name
The name of the player.
year
The year of the draft.
rank
The rank of the player in the draft.
round
The round in which the player was drafted.
date_of_birth
The date of birth of the player.
age
The age of the player at the time of the draft.
current_team
The current team of the player.
league
The league the player was playing in before the draft.
scouting_report
A scouting report of the player.
team_fit
How well the player fits with the drafting team.
likely_to_play
The likelihood of the player playing in the NHL.
position
The position the player plays.
city
The city associated with the player or team.
team
The team that selected the player.
analysis
An analysis of the player's potential and performance.
Examples
# Load the dataset
data(nhl_data)
# View the first few rows
head(nhl_data)
# Filter the data for players drafted in a specific year, e.g., 2023
nhl_2023 <- dplyr::filter(nhl_data, year == 2023)
# View the first few rows
head(nhl_2023)
# Filter the data to include only ESPN as the source
nhl_data |>
dplyr::filter(source == "ESPN")
NHL Data Base
Description
Filter NHL Data by Source (Base)
Usage
nhl_data_base()
Format
A tibble
with the following columns:
name
The name of the player.
round
The round in which the player was drafted.
rank
The rank of the player in the draft.
Details
Filters and selects NHL data from the base source for the given source value.
Value
A filtered and selected tibble of NHL data.
Examples
# Filter NHL data for base source
base_data <- nhl_data_base()
# View the first few rows
head(base_data)
NHL Data ESPN
Description
Filter NHL Data by Source (ESPN)
Usage
nhl_data_espn()
Format
A tibble
with the following columns:
name
The name of the player.
year
The year of the draft.
date_of_birth
The date of birth of the player.
age
The age of the player at the time of the draft.
current_team
The current team of the player.
league
The league the player was playing in before the draft.
scouting_report
A scouting report of the player.
team_fit
How well the player fits with the drafting team.
likely_to_play
The likelihood of the player playing in the NHL.
Details
Filters and selects NHL data from ESPN for the given source value.
Value
A filtered and selected tibble of NHL data from ESPN.
Examples
# Filter NHL data for ESPN
espn_data <- nhl_data_espn()
# View the first few rows
head(espn_data)
NHL Data NHL.com
Description
Filter NHL Data by Source (NHL.com)
Usage
nhl_data_nhl.com()
Format
A tibble
with the following columns:
name
The name of the player.
year
The year of the draft.
position
The position the player plays.
city
The city associated with the player or team.
team
The team that selected the player.
league
The league the player was playing in before the draft.
scouting_report
A scouting report of the player.
analysis
An analysis of the player's potential and performance.
Details
Filters and selects NHL data from NHL.com for the given source value.
Value
A filtered and selected tibble of NHL data from NHL.com.
Examples
# Filter NHL data for nhl.com
nhl_com_data <- nhl_data_nhl.com()
# View the first few rows
head(nhl_com_data)