---
title: "NFL Punts Analytics Position and Velocity Diagrams Cohort 1 NGS 2016 pre"
author: "Author: Roger Rosales (rosalesjrr@gmail.com)"
output:
  html_document:
    theme: cosmo
    toc: true
---

# Background
This kernel contains the Position and Velocity Diagrams for each punt concussion play in the NGS 2016 Pre dataset.

My official NFL Punts Analytics Competition write up and analysis can be found in this kernel:

<a href="https://www.kaggle.com/predact/nfl-punts-analytics-wait-and-barrier">NFL Punts Analytics Wait and Barrier</a>

Here are my other kernels for the other NFL punt plays with diagrams:

<a href="https://www.kaggle.com/predact/nfl-punts-pv-diagrams-ngs-2016-1-6">-ngs-2016-1-6</a>


```{r echo = FALSE, message=FALSE, warning=FALSE}
# Load in packages
##################################################################
library(data.table)
library(dplyr)
library(ggplot2)
library(stringr)
library(DT)
library(tidyr)
library(corrplot)
library(leaflet)
library(lubridate)
###################################################################




# Load in the NFL Punt Analytics data
####################################################################
player.punt.data <- read.csv("../input/player_punt_data.csv")
player.role.data <- read.csv("../input/play_player_role_data.csv")
play.info <- read.csv("../input/play_information.csv")
game.data <- read.csv('../input/game_data.csv')
video.review <- read.csv('../input/video_review.csv')
video_footage_injury <- read.csv("../input/video_footage-injury.csv")
video_footage_control <- read.csv("../input/video_footage-control.csv")

ngs <- read.csv("../input/NGS-2016-pre.csv")
#ngs <- read.csv("NGS-2016-reg-wk1-6.csv")
#ngs <- read.csv("NGS-2016-reg-wk7-12.csv")
#ngs <- read.csv("NGS-2016-reg-wk13-17.csv")

#For Kaggle Kernel
#player.punt.data <- read.csv("../input/player_punt_data.csv")
###################################################################






# Change classes for variables for analysis later on
###################################################################
ngs$GSISID <- as.factor(ngs$GSISID)
ngs$Time <- as.POSIXct(ngs$Time)
player.role.data$GSISID <- as.factor(player.role.data$GSISID)
#summary(ngs)
###################################################################






# Bring in Punt play information (only for manual input)
##################################################################

# gk = GameKey  
# pi = PlayId  
# gs1 = GSISID for primary player 
# gs2 = GSISID for partner player


# User input
#gk='5'
#pi='3129'
#gs1='31057'
#gs2='32482'
#pr='32482'
#pls='28284'
```

```{r echo=FALSE}
# Start of the function
puntstory <- function(gk,pi,gs1,gs2,pr,pls){


# Gather Data on the Primary and Partner players involved 
# Also manipulating the data for analysis
###################################################################


  
# Get primary player's punt role
Primary_Punt_Role <- player.role.data[player.role.data$GSISID==gs1&
                                        player.role.data$GameKey==gk&
                                        player.role.data$PlayID==pi,"Role"]

# Get primary player's activity derived
Primary_Activity <- video.review[video.review$GSISID==gs1&
                                   video.review$GameKey==gk&
                                   video.review$PlayID==pi,"Player_Activity_Derived"]

# Get primary player's impact type
Primary_Impact <- video.review[video.review$GSISID==gs1&
                                   video.review$GameKey==gk&
                                   video.review$PlayID==pi,"Primary_Impact_Type"]

# Get the flag if the concussion collision was friendly fire or not
Friendly_Fire <- video.review[video.review$GSISID==gs1&
                                 video.review$GameKey==gk&
                                 video.review$PlayID==pi,"Friendly_Fire"]


# Get partner player's punt role
Partner_Punt_Role <- player.role.data[player.role.data$GSISID==gs2&
                                        player.role.data$GameKey==gk&
                                        player.role.data$PlayID==pi,"Role"]

# Get partner player's activity derived
Partner_Activity <- video.review[video.review$GSISID==gs1&
                                   video.review$GameKey==gk&
                                   video.review$PlayID==pi,"Primary_Partner_Activity_Derived"]


# Filter the NGS data for the Primary Player and Sort by Time
primary.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                         ngs$GSISID == gs1,]

primary.allplay <- primary.allplay[order(primary.allplay$Time),]



# Filter the NGS data for the Partner Player and Sort by Time
partner.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                         ngs$GSISID == gs2,]

partner.allplay <- partner.allplay[order(partner.allplay$Time),]

# Filter the NGS data for the Punt Returner and Sort by Time
puntreturner.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                         ngs$GSISID == pr,]

puntreturner.allplay <- puntreturner.allplay[order(puntreturner.allplay$Time),]

# Filter the NGS data for the PLS line of scrimmage and Sort by Time
pls.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                              ngs$GSISID == pls,]

pls.allplay <- pls.allplay[order(pls.allplay$Time),]

# Keep track of important times during the punt
snap.time <- primary.allplay[primary.allplay$Event=="ball_snap","Time"]
punt.time <- primary.allplay[primary.allplay$Event=="punt","Time"]
punt_received.time <- primary.allplay[primary.allplay$Event=="punt_received","Time"]
fair_catch.time <- primary.allplay[primary.allplay$Event=="fair_catch","Time"]
touchback.time <- primary.allplay[primary.allplay$Event=="touchback","Time"]
oob.time <- primary.allplay[primary.allplay$Event=="out_of_bounds","Time"]
tackle.time <- primary.allplay[primary.allplay$Event=="tackle","Time"]
punt_downed.time <- primary.allplay[primary.allplay$Event=="punt_downed","Time"]

# Set the end of the punt play time by the maximum time of the ending events
end.time <-  max(punt_received.time,
                 fair_catch.time,
                 touchback.time,
                 oob.time,
                 tackle.time,
                 punt_downed.time)

#Punt location based on PLS position
pls.x <- pls.allplay[pls.allplay$Event=="ball_snap","x"]
pls.y <- pls.allplay[pls.allplay$Event=="ball_snap","y"]

#Punt Received Location
puntreturner.x <- puntreturner.allplay[puntreturner.allplay$Event=="punt_received","x"]
puntreturner.y <- puntreturner.allplay[puntreturner.allplay$Event=="punt_received","y"]

#Punt Downed Location
puntdowned.x <- puntreturner.allplay[puntreturner.allplay$Event=="punt_downed","x"]
puntdowned.y <- puntreturner.allplay[puntreturner.allplay$Event=="punt_downed","y"]

# Location of primary when punt received
primary.punt_received.x <- primary.allplay[primary.allplay$Event=="punt_received","x"]
primary.punt_received.y <- primary.allplay[primary.allplay$Event=="punt_received","y"]

# Location of partner when punt received
partner.punt_received.x <- partner.allplay[partner.allplay$Event=="punt_received","x"]
partner.punt_received.y <- partner.allplay[partner.allplay$Event=="punt_received","y"]


# Create a new data set from just the snap to the end of punt play time
primary.play <- as.data.frame(primary.allplay[primary.allplay$Time >= snap.time & primary.allplay$Time <= end.time,])

# Calculate the time since the play began
primary.play$playtime <- primary.play$Time - snap.time

table(primary.play$Event)

#str(primary.play$Event)

# OMIT: Calculate speed by MPH. Not very good because dist is not reliable.
# primary.play$mph <- primary.play$dis * (1/1760) / (0.1/3600)  

# Calculated Velocity for Primary by X and Y coordinates. Correct way
# Velocity = meters / sec  = Distance in meters / 1 second
primary.play$x_lag <- lag(primary.play$x, n = 10L) #10L to get one second change in time
primary.play$y_lag <- lag(primary.play$y, n = 10L)
primary.play$dist_meters <- 0.9144*sqrt((primary.play$x-primary.play$x_lag)^2 + (primary.play$y-primary.play$y_lag)^2)
primary.play$velocity <- primary.play$dist_meters / 1
primary.maxvelocity <- round(max(primary.play$velocity,na.rm = TRUE),digits=1)

# OMIT: Calculated MPH speed for Partner by dist column. Incorrect way.
# partner.play$mph <- partner.play$dis * (1/1760) / (0.1/3600)  

# Create partner play
partner.play <- as.data.frame(partner.allplay[partner.allplay$Time >= snap.time & partner.allplay$Time <= end.time,])

# Calculate the time since the play began
partner.play$playtime <- partner.play$Time - snap.time

# Calculated Velocity for Partner by X and Y coordinates
# 1 yard = 0.9144 meters
partner.play$x_lag <- lag(partner.play$x, n = 10L)
partner.play$y_lag <- lag(partner.play$y, n = 10L)
partner.play$dist_meters <- 0.9144*sqrt((partner.play$x-partner.play$x_lag)^2 + (partner.play$y-partner.play$y_lag)^2)
partner.play$velocity <- partner.play$dist_meters / 1
partner.maxvelocity <- round(max(partner.play$velocity,na.rm = TRUE),1)

# Primary Player Indicators
primary.play$Suffered.Concussion <- "Yes"
partner.play$Suffered.Concussion <- "No"




# Combine the primary play and the partner play
names(primary.play)
names(partner.play)
trueplay <- rbind(primary.play,partner.play)

trueplay[is.na(trueplay$velocity),"velocity"] <- 0

################################################################

#Visualize the location of the primary and partner player during the concussion play.
print(h <- ggplot(data=trueplay, aes (x=x,y=y,color=Suffered.Concussion))+
  geom_point() + 
    
    geom_vline(aes(xintercept=pls.x),
               size=5,
               color="orange")+
    annotate("text",x=pls.x,y=pls.y+2,label="Play Start")+
    
    annotate("rect", xmin = primary.punt_received.x-3, xmax = primary.punt_received.x+3, ymin = primary.punt_received.y-3, ymax = primary.punt_received.y+3,
               alpha = .2)+
    annotate("rect", xmin = partner.punt_received.x-3, xmax = partner.punt_received.x+3, ymin = partner.punt_received.y-3, ymax = partner.punt_received.y+3,
             alpha = .2)+
    
    annotate("rect", xmin = puntreturner.x-3, xmax = puntreturner.x+3, ymin = puntreturner.y-3, ymax = puntreturner.y+3,
             alpha = .2, fill="green")+
    annotate("text",x=puntreturner.x,y=puntreturner.y,label="Punt Received")+
    
    annotate("rect", xmin = puntdowned.x-3, xmax = puntdowned.x+3, ymin = puntdowned.y-3, ymax = puntdowned.y+3,
             alpha = .2, fill="green")+
    annotate("text",x=puntdowned.x,y=puntdowned.y,label="Punt Downed")+
    
    labs(title="Zoomed Paths Traveled Leading to Concussion",
       subtitle=paste("GameKey =",gk,"          PlayId=",pi,
                      "\nConcussed Player:",Primary_Punt_Role,"--",Primary_Activity,Primary_Impact," -- Maximum Velocity= ",primary.maxvelocity," m/s",
                      "\nPartner Player:",Partner_Punt_Role,"--",Partner_Activity," -- Maximum Velocity= ",partner.maxvelocity," m/s",
                      "\nFriendly Fire? ",Friendly_Fire),
       caption = paste("+++The gray box indicates the player's location when the punt was received",
                      "\nSnap time: ",snap.time,
                      "\nPunt time: ",punt.time,
                      "\nPunt Received: ",punt_received.time,
                      "\nTackle time: ",tackle.time,
                      "\nPunt Downed time: ",punt_downed.time,
                      "\nFair Catch: ",fair_catch.time,
                      "\nOut of Bounds: ",oob.time,
                      "\nTouchback: ",touchback.time),
       x = "Yards along the Home Sideline",
       y = "Yards increasing up the Endzone"
       )
  )


# Visualize the velocity of the primary and partner player 
# in meters per second
print(g <- ggplot(data=trueplay, aes(x=Time, y = velocity, color=Suffered.Concussion)) + 
  geom_line(size=2)+ 
    geom_vline(aes(xintercept=punt.time),
               size=5,
               color="orange")+

    annotate("text",x=punt.time,y=4.25,label="Punt")+
    
    geom_vline(aes(xintercept=punt_received.time),
               size=5,
               color="green")+
    annotate("text",x=punt_received.time,y=4.25,label="Punt Received")+
    
    #annotate("pointrange", x = punt_downed.time, y = 4, ymin = 0, ymax = primary.maxvelocity,
    #         colour = "green", size = 0.5)+
    #annotate("text",x=punt_received.time,y=4.25,label="Punt Received")+
    #
    
    geom_vline(aes(xintercept=tackle.time),
               size=5,
               color="red")+
    annotate("text",x=tackle.time,y=4.25,label="Tackle")+
    
    #annotate("pointrange", x = oob.time, y = 4, ymin = 0, ymax = primary.maxvelocity,
    #         colour = "black", size = 0.5)+
    #annotate("text",x=oob.time,y=4.25,label="Out of Bounds")+
    
    
    labs(title="Velocity of Players leading to the Concussion Collision",
         subtitle=paste("GameKey =",gk,"          PlayId=",pi,
                        "\nConcussed Player:",Primary_Punt_Role,"--",Primary_Activity,Primary_Impact," -- Maximum Velocity= ",primary.maxvelocity," m/s",
                        "\nPartner Player:",Partner_Punt_Role,"--",Partner_Activity," -- Maximum Velocity= ",partner.maxvelocity," m/s",
                        "\nFriendly Fire? ",Friendly_Fire),
         caption = paste("\nSnap time: ",snap.time,
                         "\nPunt time: ",punt.time,
                         "\nPunt Received: ",punt_received.time,
                         "\nTackle time: ",tackle.time,
                         "\nPunt Downed time: ",punt_downed.time,
                         "\nFair Catch: ",fair_catch.time,
                         "\nOut of Bounds: ",oob.time,
                         "\nTouchback: ",touchback.time),
         x = "Time (seconds)",
         y = "Velocity (meters per second)"
         )
  )








} 
#end of function











# Run Plays
#ngs <- read.csv("NGS-2016-pre.csv")
```

# Run Group 1 plays from the NGS 2016 pre dataset

## GameKey = 5, Play Id = 3129

```{r}
#####################################################################################
puntstory('5','3129','31057','32482','32482','28284')
```

* After the Punt was Received.
* Low tackle at knees. Concussed player hits his head on the ground.


<video width="800" height="600" controls> <source src="http://a.video.nfl.com//films/vodzilla/153233/Kadeem_Carey_punt_return-Vwgfn5k9-20181119_152809972_5000k.mp4" type="video/mp4"></video>





## GameKey = 29, Play Id = 538

```{r}
#####################################################################################
puntstory('29','538','31023','31941','31941','26493')
```

* Concussion occurred at punt received location.
* Tackle was low to knees and hit his head on the ground.



<video width="800" height="600" controls> <source src="http://a.video.nfl.com//films/vodzilla/153235/Punt_Return_by_Jamison_Crowder-HnVouDMH-20181119_153041501_5000k.mp4" type="video/mp4"></video>



## GameKey = 45, Play Id = 1212

```{r}
#####################################################################################
puntstory('45','1212','33121','28249','28249','31156')
```

* Concussion location was after the Punt was received on a rundown.
* Player tackled PR at an angle and hit his head against another body in the way. 


<video width="800" height="600" controls> <source src="http://a.video.nfl.com//films/vodzilla/153236/Punt_by_Brad_Wing-SMRxqgb2-20181119_153645589_5000k.mp4" type="video/mp4"></video>



## GameKey = 54, Play Id = 1045

```{r}
#####################################################################################
puntstory('54','1045','32444','31756','31868','23003')
```

* Concussion location was after the punt was received.
* Friendly fire
* Blindside block by a player on the Receiving Team.



<video width="800" height="600" controls> <source src="http://a.video.nfl.com//films/vodzilla/153238/Punt_Return_by_Damiere_Byrd-IX9zynRU-20181119_154215217_5000k.mp4" type="video/mp4"></video>



## GameKey = 60, Play Id = 905

```{r}
#####################################################################################
puntstory('60','905','30786','29815','32553','26844')
```

* Concussion happened at the line of scrimmage. 
* Helmet to Helmet


<video width="800" height="600" controls> <source src="http://a.video.nfl.com//films/vodzilla/153237/Punt_by_Colton_Schmidt-ujEmB7p8-20181119_153908571_5000k.mp4" type="video/mp4"></video>




## GameKey = 21, Play Id = 2587

Punt was Downed, not punt received.

* Concussion happened on the run up to the punt received area. 

<video width="800" height="600" controls> <source src="http://a.video.nfl.com//films/vodzilla/153234/Punt_by_Kasey_Redfern-w6Cpit4D-20181119_152918853_5000k.mp4" type="video/mp4"></video>



```{r echo=FALSE, message=FALSE, warning=FALSE}


# Bring in Punt play information (only for manual input)
##################################################################

# gk = GameKey  
# pi = PlayId  
# gs1 = GSISID for primary player 
# gs2 = GSISID for partner player


# User input
gk='21'
pi='2587'
gs1='29343'
gs2='31059'
pr='33132'
pls='26027'

# Start of the function
#puntstory <- function(gk,pi,gs1,gs2,pr,pls){


# Gather Data on the Primary and Partner players involved 
# Also manipulating the data for analysis
###################################################################


  
# Get primary player's punt role
Primary_Punt_Role <- player.role.data[player.role.data$GSISID==gs1&
                                        player.role.data$GameKey==gk&
                                        player.role.data$PlayID==pi,"Role"]

# Get primary player's activity derived
Primary_Activity <- video.review[video.review$GSISID==gs1&
                                   video.review$GameKey==gk&
                                   video.review$PlayID==pi,"Player_Activity_Derived"]

# Get primary player's impact type
Primary_Impact <- video.review[video.review$GSISID==gs1&
                                   video.review$GameKey==gk&
                                   video.review$PlayID==pi,"Primary_Impact_Type"]

# Get the flag if the concussion collision was friendly fire or not
Friendly_Fire <- video.review[video.review$GSISID==gs1&
                                 video.review$GameKey==gk&
                                 video.review$PlayID==pi,"Friendly_Fire"]


# Get partner player's punt role
Partner_Punt_Role <- player.role.data[player.role.data$GSISID==gs2&
                                        player.role.data$GameKey==gk&
                                        player.role.data$PlayID==pi,"Role"]

# Get partner player's activity derived
Partner_Activity <- video.review[video.review$GSISID==gs1&
                                   video.review$GameKey==gk&
                                   video.review$PlayID==pi,"Primary_Partner_Activity_Derived"]


# Filter the NGS data for the Primary Player and Sort by Time
primary.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                         ngs$GSISID == gs1,]

primary.allplay <- primary.allplay[order(primary.allplay$Time),]



# Filter the NGS data for the Partner Player and Sort by Time
partner.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                         ngs$GSISID == gs2,]

partner.allplay <- partner.allplay[order(partner.allplay$Time),]

# Filter the NGS data for the Punt Returner and Sort by Time
puntreturner.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                         ngs$GSISID == pr,]

puntreturner.allplay <- puntreturner.allplay[order(puntreturner.allplay$Time),]

# Filter the NGS data for the PLS line of scrimmage and Sort by Time
pls.allplay <- ngs[ngs$GameKey == gk & ngs$PlayID == pi &
                              ngs$GSISID == pls,]

pls.allplay <- pls.allplay[order(pls.allplay$Time),]

# Keep track of important times during the punt
snap.time <- primary.allplay[primary.allplay$Event=="ball_snap","Time"]
punt.time <- primary.allplay[primary.allplay$Event=="punt","Time"]
punt_received.time <- primary.allplay[primary.allplay$Event=="punt_received","Time"]
fair_catch.time <- primary.allplay[primary.allplay$Event=="fair_catch","Time"]
touchback.time <- primary.allplay[primary.allplay$Event=="touchback","Time"]
oob.time <- primary.allplay[primary.allplay$Event=="out_of_bounds","Time"]
tackle.time <- primary.allplay[primary.allplay$Event=="tackle","Time"]
punt_downed.time <- primary.allplay[primary.allplay$Event=="punt_downed","Time"]

# Set the end of the punt play time by the maximum time of the ending events
end.time <-  max(punt_received.time,
                 fair_catch.time,
                 touchback.time,
                 oob.time,
                 tackle.time,
                 punt_downed.time)

#Punt location based on PLS position
pls.x <- pls.allplay[pls.allplay$Event=="ball_snap","x"]
pls.y <- pls.allplay[pls.allplay$Event=="ball_snap","y"]

#Punt Received Location
puntreturner.x <- puntreturner.allplay[puntreturner.allplay$Event=="punt_received","x"]
puntreturner.y <- puntreturner.allplay[puntreturner.allplay$Event=="punt_received","y"]

#Punt Downed Location
puntdowned.x <- puntreturner.allplay[puntreturner.allplay$Event=="punt_downed","x"]
puntdowned.y <- puntreturner.allplay[puntreturner.allplay$Event=="punt_downed","y"]

# Location of primary when punt received
primary.punt_received.x <- primary.allplay[primary.allplay$Event=="punt_received","x"]
primary.punt_received.y <- primary.allplay[primary.allplay$Event=="punt_received","y"]

# Location of partner when punt received
partner.punt_received.x <- partner.allplay[partner.allplay$Event=="punt_received","x"]
partner.punt_received.y <- partner.allplay[partner.allplay$Event=="punt_received","y"]


# Create a new data set from just the snap to the end of punt play time
primary.play <- as.data.frame(primary.allplay[primary.allplay$Time >= snap.time & primary.allplay$Time <= end.time,])

# Calculate the time since the play began
primary.play$playtime <- primary.play$Time - snap.time

#table(primary.play$Event)

#str(primary.play$Event)

# OMIT: Calculate speed by MPH. Not very good because dist is not reliable.
# primary.play$mph <- primary.play$dis * (1/1760) / (0.1/3600)  

# Calculated Velocity for Primary by X and Y coordinates. Correct way
# Velocity = meters / sec  = Distance in meters / 1 second
primary.play$x_lag <- lag(primary.play$x, n = 10L) #10L to get one second change in time
primary.play$y_lag <- lag(primary.play$y, n = 10L)
primary.play$dist_meters <- 0.9144*sqrt((primary.play$x-primary.play$x_lag)^2 + (primary.play$y-primary.play$y_lag)^2)
primary.play$velocity <- primary.play$dist_meters / 1
primary.maxvelocity <- round(max(primary.play$velocity,na.rm = TRUE),digits=1)

# OMIT: Calculated MPH speed for Partner by dist column. Incorrect way.
# partner.play$mph <- partner.play$dis * (1/1760) / (0.1/3600)  

# Create partner play
partner.play <- as.data.frame(partner.allplay[partner.allplay$Time >= snap.time & partner.allplay$Time <= end.time,])

# Calculate the time since the play began
partner.play$playtime <- partner.play$Time - snap.time

# Calculated Velocity for Partner by X and Y coordinates
# 1 yard = 0.9144 meters
partner.play$x_lag <- lag(partner.play$x, n = 10L)
partner.play$y_lag <- lag(partner.play$y, n = 10L)
partner.play$dist_meters <- 0.9144*sqrt((partner.play$x-partner.play$x_lag)^2 + (partner.play$y-partner.play$y_lag)^2)
partner.play$velocity <- partner.play$dist_meters / 1
partner.maxvelocity <- round(max(partner.play$velocity,na.rm = TRUE),1)

# Primary Player Indicators
primary.play$Suffered.Concussion <- "Yes"
partner.play$Suffered.Concussion <- "No"




# Combine the primary play and the partner play
# names(primary.play)
# names(partner.play)
trueplay <- rbind(primary.play,partner.play)

trueplay[is.na(trueplay$velocity),"velocity"] <- 0

################################################################



print(h <- ggplot(data=trueplay, aes (x=x,y=y,color=Suffered.Concussion))+
  geom_point() + 
    
    geom_vline(aes(xintercept=pls.x),
               size=5,
               color="orange")+
    annotate("text",x=pls.x,y=pls.y+2,label="Play Start")+
    
    #annotate("rect", xmin = primary.punt_received.x-3, xmax = primary.punt_received.x+3, ymin = primary.punt_received.y-3, ymax = primary.punt_received.y+3,
    #           alpha = .2)+
    #annotate("rect", xmin = partner.punt_received.x-3, xmax = partner.punt_received.x+3, ymin = partner.punt_received.y-3, ymax = partner.punt_received.y+3,
    #         alpha = .2)+
    
    #annotate("rect", xmin = puntreturner.x-3, xmax = puntreturner.x+3, ymin = puntreturner.y-3, ymax = puntreturner.y+3,
    #         alpha = .2, fill="green")+
    #annotate("text",x=puntreturner.x,y=puntreturner.y,label="Punt Received")+
    
    annotate("rect", xmin = puntdowned.x-3, xmax = puntdowned.x+3, ymin = puntdowned.y-3, ymax = puntdowned.y+3,
             alpha = .2, fill="green")+
    annotate("text",x=puntdowned.x,y=puntdowned.y,label="Punt Downed")+
    
    labs(title="Zoomed Paths Traveled Leading to Concussion",
       subtitle=paste("GameKey =",gk,"          PlayId=",pi,
                      "\nConcussed Player:",Primary_Punt_Role,"--",Primary_Activity,Primary_Impact," -- Maximum Velocity= ",primary.maxvelocity," m/s",
                      "\nPartner Player:",Partner_Punt_Role,"--",Partner_Activity," -- Maximum Velocity= ",partner.maxvelocity," m/s",
                      "\nFriendly Fire? ",Friendly_Fire),
       caption = paste("+++The gray box indicates the player's location when the punt was received",
                      "\nSnap time: ",snap.time,
                      "\nPunt time: ",punt.time,
                      "\nPunt Received: ",punt_received.time,
                      "\nTackle time: ",tackle.time,
                      "\nPunt Downed time: ",punt_downed.time,
                      "\nFair Catch: ",fair_catch.time,
                      "\nOut of Bounds: ",oob.time,
                      "\nTouchback: ",touchback.time),
       x = "Yards along the Home Sideline",
       y = "Yards increasing up the Endzone"
       )
  )


# Visualize the velocity of the primary and partner player 
# in meters per second
print(g <- ggplot(data=trueplay, aes(x=Time, y = velocity, color=Suffered.Concussion)) + 
  geom_line(size=2)+ 
    geom_vline(aes(xintercept=punt.time),
               size=5,
               color="orange")+

    annotate("text",x=punt.time,y=4.25,label="Punt")+
    
    #geom_vline(aes(xintercept=punt_received.time),
    #           size=5,
    #           color="green")+
    #annotate("text",x=punt_received.time,y=4.25,label="Punt Received")+
    
    geom_vline(aes(xintercept=punt_downed.time),
               size=5,
               color="orange")+
    annotate("text",x=punt_downed.time,y=4.25,label="Punt Downed")+
    #
    
    #geom_vline(aes(xintercept=tackle.time),
    #           size=5,
    #           color="red")+
    #annotate("text",x=tackle.time,y=4.25,label="Tackle")+
    
    #annotate("pointrange", x = oob.time, y = 4, ymin = 0, ymax = primary.maxvelocity,
    #         colour = "black", size = 0.5)+
    #annotate("text",x=oob.time,y=4.25,label="Out of Bounds")+
    
    
    labs(title="Velocity of Players leading to the Concussion Collision",
         subtitle=paste("GameKey =",gk,"          PlayId=",pi,
                        "\nConcussed Player:",Primary_Punt_Role,"--",Primary_Activity,Primary_Impact," -- Maximum Velocity= ",primary.maxvelocity," m/s",
                        "\nPartner Player:",Partner_Punt_Role,"--",Partner_Activity," -- Maximum Velocity= ",partner.maxvelocity," m/s",
                        "\nFriendly Fire? ",Friendly_Fire),
         caption = paste("\nSnap time: ",snap.time,
                         "\nPunt time: ",punt.time,
                         "\nPunt Received: ",punt_received.time,
                         "\nTackle time: ",tackle.time,
                         "\nPunt Downed time: ",punt_downed.time,
                         "\nFair Catch: ",fair_catch.time,
                         "\nOut of Bounds: ",oob.time,
                         "\nTouchback: ",touchback.time),
         x = "Time (seconds)",
         y = "Velocity (meters per second)"
         )
  )

```