449Scouting2025.qmd

---
title: "449 Scouting 2025"
format: html
editor: visual
params:
    red1: 449
    red2: 451
    red3: 456
    blue1: 487
    blue2: 483
    blue3: 453
---

```{r setup, message=FALSE, warning=FALSE}
#rm(list = setdiff(ls(),"params"))

library(tidyverse)

blair_red <- "#a7000a"

red_alliance <- c(params$red1, params$red2, params$red3)
blue_alliance <- c(params$blue1, params$blue2, params$blue3)

 raw <- read_csv("made_up_data.csv")

```

BOX PLOT OF ALL TOTAL POINTS

```{r}
boxplot <- raw %>%
  filter(team %in% c(red_alliance, blue_alliance)) %>%
 mutate(team = factor(team, c(red_alliance,blue_alliance) ))%>%
   
  mutate(total_coral_score = 
           (coral_L1_num*2) + (coral_L2_num*3) + 
           (coral_L3_num*4) + (coral_L4_num*5) + 
           (auto_coral_L1_num*3) + (auto_coral_L2_num*4)+ 
           (auto_coral_L3_num*5)+ (auto_coral_L4_num*7),
         
         total_algea_score = 
           (robot_net_score*4) + (proc_score*2.5),
         
         total_endgame_score = 
           ifelse(ending =="D", 12, ifelse(ending=="S",6,ifelse(ending=="P", 2, 0)))
           )

  boxplot$total = boxplot$total_algea_score + boxplot$total_coral_score+boxplot$total_endgame_score


 ggplot(boxplot,aes(x = total, y = as.character(team)))+
 geom_boxplot(position = "dodge2", fill = "azure2", ) +
   stat_boxplot(geom = "errorbar")+
   stat_summary(fun.y = mean, geom="point", size=3, color="orange",)+
#   geom_point(aes(x =total_mean, y = team ), color = 'orange', size = 2)
  
    
       labs(title = "Total points scored",
          x = "Point", y = "Team")+
    
  theme_bw()
```

BUBBLE GRAPH OF EVERYTHING

```{r}
bubble <- raw%>%
  group_by(team)%>%
  summarise(
    match = n(),
            total_coral_score = sum(
        (auto_coral_L1_num*3) + (auto_coral_L2_num*4) + (auto_coral_L3_num*6) + (auto_coral_L4_num*7) + 
         (coral_L1_num*2) + (coral_L2_num*3) + (coral_L3_num*4)+ (coral_L4_num*5)),
      
       total_algea_score = sum(
           (robot_net_score*4) + (proc_score*2.5)),
         
       endgame_score = sum(
           ifelse(ending =="D", 12, ifelse(ending =="S",6,ifelse(ending =="P", 2, 0)))),
)

ggplot(bubble, aes(x=total_coral_score, y=total_algea_score, size = endgame_score)) +
    geom_point( color = "lightblue2")+
  geom_text( aes(label=team, vjust = 1.7 ))+
  labs(title = "Teams Performance Summary", 
          x = "Auto + Tele Coral Points", y = "Total Algea Points", fill = "Auto+End", size = "Endgame")
```

CORAL LEVEL SCORING

```{r}
 bar <- raw %>%
     filter(team %in% c(red_alliance, blue_alliance)) %>%
    mutate(team = factor(team, c(red_alliance,blue_alliance) )) %>%

  group_by(team) %>%
  summarize(
    l1 = mean(coral_L1_num),
    l2 = mean(coral_L2_num),
    l3 = mean(coral_L3_num),
    l4 = mean(coral_L4_num)
  
  )%>%
    pivot_longer(cols = c(l4, l3, l2,l1), 
                    names_to = "level", 
                 values_to = "coral_num")
 
bar$level_score <- case_when(
  bar$level == "l1" ~ bar$coral_num*2, 
  bar$level == "l2" ~ bar$coral_num*3, 
  bar$level == "l3" ~ bar$coral_num*4, 
  bar$level == "l4" ~ bar$coral_num*5, 
)

  ggplot(bar, aes(x = `team`, y = level_score, fill = level)) + 
     geom_bar(position = "stack", stat = "identity") + 
     labs(title = "Level Summary", 
          x = "Team", y = "Coral score", fill = "Level") +
    scale_fill_manual(values=c("lightskyblue","royalblue1","royalblue3","navy"))+
     theme_bw()
```

CORAL SCORED DURING AUTO AND TELEOP

```{r}
 auto_tele <- raw %>%
   filter(team %in% c(red_alliance, blue_alliance)) %>%
    mutate(team = factor(team, c(red_alliance,blue_alliance) )) %>%
   
  group_by(team) %>%
  summarize(
    matches = n(),
  
    l1 = mean(coral_L1_num),
    l2 = mean(coral_L2_num),
    l3 = mean(coral_L3_num),
    l4 = mean(coral_L4_num),
    autol1 = mean(auto_coral_L1_num),
    autol2 = mean(auto_coral_L2_num),
    autol3 = mean(auto_coral_L3_num),
    autol4 = mean(auto_coral_L4_num)
  
  )%>%

       pivot_longer(cols = c(l4, l3, l2,l1,autol1,autol2,autol3,autol4), 
                 names_to = "level", 
                 values_to = "coral_num")
 auto_tele$level_score <- case_when(
  auto_tele$level == "l1" ~ auto_tele$coral_num*2, 
  auto_tele$level == "l2" ~ auto_tele$coral_num*3, 
  auto_tele$level == "l3" ~ auto_tele$coral_num*4, 
  auto_tele$level == "l4" ~ auto_tele$coral_num*5,
  auto_tele$level == "autol1" ~ auto_tele$coral_num*3,
  auto_tele$level == "autol2" ~ auto_tele$coral_num*4,
  auto_tele$level == "autol3" ~ auto_tele$coral_num*6,
  auto_tele$level == "autol4" ~ auto_tele$coral_num*7

)

  ggplot(auto_tele, aes(x = `team`, y = (level_score), fill = level)) + 
     geom_bar(position = "stack", stat = "identity") + 
     labs(title = "Level Summary", 
          x = "Team", y = "Coral score", fill = "Level") +
    scale_fill_manual(values=c("plum1","plum2","plum3","plum4","steelblue2","steelblue3","steelblue","steelblue4"))+
   
   theme_bw() 
  

```

ENDGAME SCORING

```{r}
end <- raw %>%
   filter(team %in% c(red_alliance, blue_alliance)) %>%
    mutate(team = factor(team, c(red_alliance,blue_alliance) )) %>%

    group_by(team, ending) %>%
  summarise(count = n())

end$points <- recode(end$ending,  "P" = 2, "S" = 6, "D" = 12, "No" = 0, "F" = 0)

#compute the total end game score from all matches
end$total_points <- end$count * end$points

end$ending <- factor(end$ending, levels = c("D", "S","P","F","No"))

ggplot(end, aes(x =team, y = total_points, fill = ending)) +
  geom_bar(position= "stack", stat = "identity") +
  
  labs(title = "Endgame Score",
       x = "Team",
       y = "Points") +
  scale_fill_manual(
    values = c("D" = "springgreen4", "S" = "olivedrab3", "P" = "#FFF68F"),
    labels = c("D" = "Deep", "S" = "Shallow", "P" = "Park", "ending" = "Cage"),
  )
```


```{r}
proc <- read_csv("procReturns.csv")
net <- read_csv("netReturns.csv")

both <- data.frame(Processor = proc[[1]], Net = net[[1]])
both$Index <- seq_len(nrow(both))  

ggplot(both, aes(x = Processor, y = Net, label = Index)) +
  geom_point(color = blair_red) +     
  geom_line(color = blair_red) +     
  geom_text(vjust = -0.5, hjust = 1.2, color = "black") +  
  geom_abline(slope = 1, intercept = 0, linetype = "dashed", color = "blue") +  
  labs(x = "Processor Returns", y = "Net Returns", title = "Net Vs Processor") +
  theme_minimal()

```