Help for package pinnacle.data

Type:

Package

Title:

Market Odds Data from Pinnacle

Version:

0.1.4

Author:

Marco Blume, Michael Yan

Maintainer:

Marco Blume <marco.blume@pinnaclesports.com>

Description:

Market odds from from Pinnacle, an online sports betting bookmaker (see https://www.pinnacle.com for more information). Included are datasets for the Major League Baseball (MLB) 2016 season and the USA election 2016. These datasets can be used to build models and compare statistical information with the information from prediction markets.The Major League Baseball (MLB) 2016 dataset can be used for sabermetrics analysis and also can be used in conjunction with other popular Major League Baseball (MLB) datasets such as Retrosheets or the Lahman package by merging by GameID.

License:

GPL-3

Encoding:

UTF-8

LazyData:

true

RoxygenNote:

6.0.1

URL:

https://github.com/marcoblume/pinnacle.data

Depends:

R (≥ 2.10), tibble

Suggests:

odds.converter, tidyverse, pinnacle.API, Lahman

NeedsCompilation:

Packaged:

2017-06-29 13:46:09 UTC; MarcoB

Repository:

CRAN

Date/Publication:

2017-06-29 15:30:31 UTC

MLB2016.

Description

Major League Baseball (MLB) data for the 2016 season.

Usage

MLB2016

Format

A tibble with 20 variables:

GameID: same format as Retrosheets and BaseballReference data
EventDateTimeUTC: Time of the game in UTC
EventDateTimeET: Time of the game in Eastern Standardtime
AwayTeam: Team name of the Away Team
HomeTeam: Team name of the Home Team
DoubleHeaderGame: Indicates if this was a double Header
AwayStartingPitcher: Starting pitcher Away Team
HomeStartingPicher: Starting pitcher Home Team
FinalScoreAway: Runs scored by Away Team
FinalScoreHome: Runs scored by Home Team
EnteredDateTimeUTC: Time of the wager line in UTC
EnteredDateTimeET: Time of the wager line in Eastern Standardtime
SpreadTeam1: Spread Handicap for Away Team
SpreadUS1: Spread US odds for Away Team
SpreadUS2: Spread US odds for Home Team
MoneyUS1: Moneyline US odds for Away Team
MoneyUS2: Moneyline US odds for Home Team
TotalPoints: Total runs handicap
TotalUSOver: Total runs US odds for Over
TotalUSUnder: Total runs US odds for Under

Details

All wagering lines from Pinnacle for the 2016 MLB season

Examples

if (require("tidyverse")) {
library(tidyverse)
# What was the range of expected total runs according to the prediction market at Pinnacle?
MLB2016 %>% 
 unnest() %>% 
 group_by(GameID) %>% 
 arrange(desc(EnteredDateTimeUTC)) %>% 
 slice(1) %>% 
 ungroup() %>% 
 group_by(TotalPoints) %>% 
 summarize(Count = n())

# How many games went Over/Under/Landed on the total?
MLB2016 %>% 
 unnest() %>% 
 group_by(GameID) %>% 
 arrange(desc(EnteredDateTimeUTC)) %>% 
 slice(1) %>% 
 ungroup() %>% 
 select(GameID,TotalPoints,FinalScoreAway,FinalScoreHome) %>% 
 mutate(TotalOutcome = case_when(
   FinalScoreAway + FinalScoreHome > TotalPoints ~ "Over",
   FinalScoreAway + FinalScoreHome < TotalPoints ~ "Under",
   FinalScoreAway + FinalScoreHome == TotalPoints ~ "Landed"
 )
 ) %>% 
 group_by(TotalPoints,TotalOutcome) %>% 
 summarize(Count = n()) %>% 
 print(n=100)
}

USA_Election_2016

Description

US Presidential Election data 2016.

Usage

USA_Election_2016

Format

A data.frame with 5 variables:

EnteredDateTime: Time of the wager line in UTC
TeamName1: Team name of the Away Team
TeamName2: Team name of the Home Team
MoneyUS1: Moneyline US odds for Away Team
MoneyUS2: Moneyline US odds for Home Team

Details

All lines from Pinnacle for the 2016 US Presidential Election

Examples

if (require("odds.converter")) {
library(tidyverse)
# What is Hilary Clinton's the highest implied winning probability at Pinnacle?

USA_Election_2016[which.min(USA_Election_2016$MoneyUS1),"EnteredDateTime"]
odds.converter::odds.us2prob(min(USA_Election_2016$MoneyUS1))
}

# What time on election night that Trump's implied winning probability surpassed Clinton's?
if (require("tidyverse")) {
library(tidyverse)
USA_Election_2016 %>% 
 filter(MoneyUS1>MoneyUS2) %>%
 slice(1)
}