Help for package ProSportsDraftData

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:

Depends:

R (≥ 3.5.0)

VignetteBuilder:

knitr

License:

GPL-3

NeedsCompilation:

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

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)

ProSportsDraftData: Professional Sports Draft Data

Description

Author(s)

See Also

NBA Draft Data

Description

Usage

Format

Examples

NBA Data Base

Description

Usage

Format

Details

Value

Examples

NBA Data ESPN

Description

Usage

Format

Details

Value

Examples

NBA Data NBA.com

Description

Usage

Format

Details

Value

Examples

NBA Data NBADraft.net

Description

Usage

Format

Details

Value

Examples

NBA Data The Ringer

Description

Usage

Format

Details

Value

Examples

NFL Draft Data

Description

Usage

Format

Examples

NFL Data Base

Description

Usage

Format

Details

Value

Examples

NFL Data ESPN

Description

Usage

Format

Details

Value

Examples

NFL Data NFL.com

Description

Usage

Format

Details

Value

Examples

NFL Data The Ringer

Description

Usage

Format

Details

Value

Examples

NFL Data Walter Football

Description

Usage