https://github.com/papagorgio23/3point_vs_2point
Down by 3 with 30 seconds left in the game. Do you go for a quick 2 point shot and foul? or should you go for a 3? This simulation will help us determine what is the best course of action.
https://github.com/papagorgio23/3point_vs_2point
Last synced: 6 months ago
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Down by 3 with 30 seconds left in the game. Do you go for a quick 2 point shot and foul? or should you go for a 3? This simulation will help us determine what is the best course of action.
- Host: GitHub
- URL: https://github.com/papagorgio23/3point_vs_2point
- Owner: papagorgio23
- License: mit
- Created: 2018-06-27T05:50:37.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2020-01-17T17:57:36.000Z (over 5 years ago)
- Last Synced: 2023-07-25T04:29:43.868Z (almost 2 years ago)
- Language: Jupyter Notebook
- Size: 25.4 KB
- Stars: 5
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
3 pointer or 2 points and foul
------------------------------
trials <- 25000 ## Number of trials to run for simulation
timeLeft <- 30
pointsDown <- 3
threePtPercent <- 35 # Your % chance of making 3-pt shot
twoPtPercent <- 45 # Your % chance of making a 2-pt shot
oppTwoPtPercent <- 40 # Opponent % chance making 2-pter
oppFtPercent <- 80 # Opponent's FT %
timeToShoot2 <- 5 # How many seconds elapse to shoot a 2
timeToFoul <- 3 # How many seconds elapse to foul opponent
offenseReboundPercent <- 25 # % of regular offense rebound
ftReboundPercent <- 15 # % of offense rebound after missed FT
overtimePercent <- 50 # % chance of winning in overtime
i = 1 # initialize the simulation
Including Plots
---------------
You can also embed plots, for example:
## takeThree determines if we win in a given trial when we take a 3. We first see if we make the 3. Then we see if we can win in overtime
takeThree <- function() {
if (sample(0:100, 1) <= threePtPercent) {
if (sample(0:100, 1) <= overtimePercent) {
return (TRUE) # We won!!
}
}
return (FALSE) # We either missed the 3 or lost in OT
}
takeTwo <- function() {
havePossession <- TRUE
while(timeLeft > 0) {
## What to do if we have possession
if (havePossession) {
# If we are down by 3 or more, we take the
# 2 quickly. If we are down by 2 or less
# We run down the clock first
if (pointsDown >= 3) {
timeLeft = timeLeft - timeToShoot2
} else {
timeLeft = 0
}
## Do we make the shot?
if (sample(0:100, 1) <= twoPtPercent) {
pointsDown = pointsDown - 2
havePossession = FALSE
} else {
# Does the opponent team rebound?
# If so, we lose possession.
# This doesn't really matter when we run
# the clock down
if (sample(0:100, 1) >= offenseReboundPercent) {
havePossession = FALSE
}
}
} else {
# cases where we don't have possession
if (pointsDown > 0) {
# foul to get back possession
# takes time to foul
timeLeft = timeLeft - timeToFoul
# opponent takes 2 free throws
if (sample(0:100, 1) < oppFtPercent) {
pointsDown = pointsDown + 1
}
if (sample(0:100, 1) < oppFtPercent) {
pointsDown = pointsDown + 1
havePossession = TRUE
} else if (sample(0:100, 1) >= ftReboundPercent) {
# you were able to rebound the missed ft
havePossession = TRUE
}
} else {
# tied or up so don't want to foul; assume opponent to run out clock and take
if (sample(0:100, 1) < oppTwoPtPercent) {
pointsDown = pointsDown + 2 # They made the 2
}
timeLeft = 0
}
}
}
## now get the result of the sim
if (pointsDown > 0) {
return(FALSE) # you lost
} else if (pointsDown < 0) {
return (TRUE) # you won
} else {
if (sample(0:100, 1) < overtimePercent) {
return(TRUE) # you won in overtime
} else {
return (FALSE) # you lost in overtime
}
}
}
Run Sim
-------
takeThree()
## [1] FALSE
takeTwo()
## [1] FALSE
Function to run both Sims
-------------------------
set.seed(1234)
simulation.results <- c()
while(i <= trials) {
winsTakingThree <- 0
lossTakingThree <- 0
winsTakingTwo <- 0
lossTakingTwo <- 0
curTrial <- 0
if (curTrial < trials) {
# run a trial take the 3
if (takeThree()) {
# did we win taking a 3?
winsTakingThree = winsTakingThree + 1 # increment the wins
} else {
lossTakingThree = lossTakingThree + 1
}
# run a trial taking a 2
if (takeTwo()) {
winsTakingTwo = winsTakingTwo + 1
} else {
lossTakingTwo = lossTakingTwo + 1
}
curTrial = curTrial + 1
}
final <- c(winsTakingThree, lossTakingThree, winsTakingTwo, lossTakingTwo)
simulation.results <- c(simulation.results, final)
i <- i + 1
}
sim.results.mat <- matrix(simulation.results, ncol=4, byrow=TRUE)
sim.results.df <- as.data.frame(sim.results.mat)
names(sim.results.df) <- c(
"winsTakingThree", "lossTakingThree",
"winsTakingTwo", "lossTakingTwo")
summary(sim.results.df)
## winsTakingThree lossTakingThree winsTakingTwo lossTakingTwo
## Min. :0.0000 Min. :0.0000 Min. :0.00000 Min. :0.0000
## 1st Qu.:0.0000 1st Qu.:1.0000 1st Qu.:0.00000 1st Qu.:1.0000
## Median :0.0000 Median :1.0000 Median :0.00000 Median :1.0000
## Mean :0.1809 Mean :0.8191 Mean :0.06852 Mean :0.9315
## 3rd Qu.:0.0000 3rd Qu.:1.0000 3rd Qu.:0.00000 3rd Qu.:1.0000
## Max. :1.0000 Max. :1.0000 Max. :1.00000 Max. :1.0000
perrcentResult <- sim.results.df %>%
summarise(winsTakingThree = paste0(round(100*mean(winsTakingThree), 2), "%"),
lossTakingThree = paste0(round(100*mean(lossTakingThree), 2), "%"),
winsTakingTwo = paste0(round(100*mean(winsTakingTwo), 2), "%"),
lossTakingTwo = paste0(round(100*mean(lossTakingTwo), 2), "%"))
perrcentResult
## winsTakingThree lossTakingThree winsTakingTwo lossTakingTwo
## 1 18.09% 81.91% 6.85% 93.15%
sumResult <- sapply(sim.results.df, sum)
barplot(sumResult)
