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This package includes functions to transform sports betting odds from one format into another.
These betting odds formats are covered in odds.converter at the moment
Please contact me if there is a betting odds format that needs to be added to this package.
Fractional Odds commonly used by bookmakers in the U.K. are not included as the transformation of these Odds is not very well defined and Fractional Odds are not used outside of the U.K and have been largely replaced by Decimal Odds.
# Install from Cran
install.packages("odds.converter")
# Or the the development version from GitHub:
# install.packages("devtools")
devtools::install_github("marcoblume/odds.converter")
The package contains functions to transform one specific odds type into another specific odds type. These functions are called:
odds.Shortform2Shortform
For example
library(odds.converter)
odds.us2dec(-115)
odds.prob2malay(0.5)
odds.indo2hk(0.8)
To transform a specific odds type into all other odds type use the functions that are called odds.Shortform2all
For example
library(odds.converter)
odds.dec2all(-115)
odds.prob2all(0.5)
odds.indo2all(0.8)
Bookmakers will include a margin to their betting odds that will increase the total probability of the offered odds above 100%. If a bookmaker would offer a coin flip instead of offering 50% for heads and 50% for tails the bookmaker would have 51% for heads and 51% for tails for example thus guaranteeing that they would make a small profit for every wager on the coin flip.
odds.prob2dec(0.51)
To calculate the margin that bookmaker offers convert the odds into probability and sum them.
Betting Odds:
Manchester United Decimal Odds 1.3 Arsenal Decimal Odds 9.0 Draw Decimal Odds 4.0
sum(odds.dec2prob(c(1.3,9,4)))
1.130342
The build margin is slightly over 13%
To calculate the real implied probability use the function odds.fv()
Example: Calculate the implied probability of the above match without margin added
odds.fv(1.3,9,4,input = "dec",output = "dec")
1.469444 10.173077 4.521368
Example: Calculate the implied probability of the above match without margin added
odds.fv(1.3,9,4,input = "dec",output = "prob")
0.68052930 0.09829868 0.22117202
Example: Calculate the implied probability of a data.frame containing Home and Away odds
df <- data.frame(Home = c(1.5,1.8,1.9),
Away = c(2.9,2.2,2.05))
odds.fv(df,input = "dec",output = "prob")
Home Away
[1,] 0.6590909 0.3409091
[2,] 0.5500000 0.4500000
[3,] 0.5189873 0.4810127
It is also possible to submit vectors as input to calculate the implied Probability
odds.fv(df$Home,df$Away,input="dec",output="prob")
Example: Calculate the implied probablity of home and away lines with dplyr
library(dplyr)
df <- data.frame(Home = c(1.5,1.8,1.9),
Away = c(2.9,2.2,2.05))
df %>%
rowwise() %>%
mutate(FairHome = odds.fv(Home,Away,
input = "dec",
output = "prob")[1]) %>%
mutate(FairAway = 1 - FairHome)
As rowwise() slows down the calculation and the calculation of fair values for Home and Away odds is a common use case odds.fv() has an option (Vectorized2wayOutput1stElement = TRUE), which can speed up the computation significantly for this specific use case.
df %>%
mutate(FairHome = odds.fv(Home,Away,
input = "dec",
output = "prob",
Vectorized2wayOutput1stElement = TRUE)) %>%
mutate(FairAway = 1 - FairHome)
To calculate the fair price for a parlay input the betting odds of each of the parlay legs and use odds.parlay()
```{r} odds.parlay(c(-105,-110),output=“dec”)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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