MLB2016: MLB2016.
In pinnacle.data: Market Odds Data from Pinnacle

Description Usage Format Details Examples

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

MLB2016

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

All wagering lines from Pinnacle for the 2016 MLB season

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)
}

Loading required package: tibble
Loading required package: tidyverse
-- Attaching packages --------------------------------------- tidyverse 1.2.1 --
v ggplot2 3.1.1       v purrr   0.3.2  
v tidyr   0.8.3       v dplyr   0.8.0.1
v readr   1.3.1       v stringr 1.4.0  
v ggplot2 3.1.1       v forcats 0.4.0  
-- Conflicts ------------------------------------------ tidyverse_conflicts() --
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
# A tibble: 37 x 3
# Groups:   TotalPoints [16]
   TotalPoints TotalOutcome Count
         <dbl> <chr>        <int>
 1         5.5 Under            2
 2         6   Over             7
 3         6   Under            9
 4         6.5 Over            30
 5         6.5 Under           24
 6         7   Landed          19
 7         7   Over            91
 8         7   Under           86
 9         7.5 Over           234
10         7.5 Under          230
11         8   Landed          31
12         8   Over           212
13         8   Under          178
14         8.5 Over           249
15         8.5 Under          264
16         9   Landed          52
17         9   Over           186
18         9   Under          187
19         9.5 Over            84
20         9.5 Under           96
21        10   Landed           5
22        10   Over            33
23        10   Under           36
24        10.5 Over            16
25        10.5 Under           30
26        11   Landed           2
27        11   Over            12
28        11   Under           10
29        11.5 Over            10
30        11.5 Under            8
31        12   Landed           2
32        12   Over             4
33        12   Under            5
34        12.5 Over             7
35        12.5 Under            8
36        13   Landed           1
37        13   Over             2