records-bowling.Rmd

---
title: "Bowling Records"
description: |
  A collection of various records throughout our history! 
author:
  - name: James Day
date: "`r Sys.Date()`"
output: distill::distill_article
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
	echo = FALSE,
	message = FALSE,
	warning = FALSE
)
library(dplyr)
library(readr)
library(purrr)
library(stringr)
library(here)
library(reactable)
library(htmltools)
library(knitr)
library(rmarkdown)
```

```{r load data, include=FALSE, echo = FALSE}

bowling <- read_csv(here::here("data", "bowling_combined.csv"))
```


```{r summarise-data-all}
bowling <- bowling %>%
  mutate(Opposition = ifelse(home_team == "The Nutty Cuckoo Super Kings", away_team, home_team),
         `3s` = ifelse(Wkts >= 3, 1, 0),
         `5s` = ifelse(Wkts >= 5 , 1, 0),
         date = format(date, "%d/%m/%Y")) %>%
  filter(team == "The Nutty Cuckoo Super Kings")

df_all <- bowling %>%
  group_by(Bowlers) %>%
  summarise(innings = n(),
            Overs = sum(Overs, na.rm = TRUE),
            Balls = ceiling(sum(Overs, na.rm = TRUE)*6),
            Runs = sum(Runs, na.rm = TRUE),
            Wkts = sum(Wkts, na.rm = TRUE),
            SR = Balls/sum(Wkts, na.rm = TRUE),
            Avg = Runs/Wkts,
            Econ = Runs/sum(Overs, na.rm = TRUE),
            `3` = sum(`3s`, na.rm = TRUE),
            `5` = sum(`5s`, na.rm = TRUE)) %>%
  rename(Name = Bowlers) 

best_bowling <- bowling %>% 
  rename(Name = Bowlers) %>%
  group_by(Name) %>% 
  filter(Wkts == max(Wkts)) %>% 
  filter(Runs == min(Runs)) %>% 
  filter(row_number(Runs) == 1) %>%
  mutate(BB = paste0(Wkts, "/", Runs)) 

best_bowling_df <- best_bowling %>%
  select(Name, BB)

df_all <- df_all %>%
  left_join(best_bowling_df, by = "Name")
df_all[df_all == "Inf" ] <- NA
```

```{r summarise-data-seas}
df_seas <- bowling %>%
  group_by(season, Bowlers) %>%
  summarise(innings = n(),
            Overs = sum(Overs, na.rm = TRUE),
            Balls = ceiling(sum(Overs, na.rm = TRUE)*6),
            Runs = sum(Runs, na.rm = TRUE),
            Wkts = sum(Wkts, na.rm = TRUE),
            SR = Balls/sum(Wkts, na.rm = TRUE),
            Avg = Runs/Wkts,
            Econ = Runs/sum(Overs, na.rm = TRUE),
            `3` = sum(`3s`, na.rm = TRUE),
            `5` = sum(`5s`, na.rm = TRUE)) %>%
  rename(Name = Bowlers) 

df_seas[df_seas == "Inf" ] <- NA
```

# Best Bowling (innings)
```{r}
bowling %>%
  arrange(desc(Wkts), Runs) %>%
  mutate(BB = paste0(Wkts, "/", Runs)) %>%
  ungroup() %>%
  filter(row_number(desc(Wkts)) < 6) %>%
  select(date, Bowlers, Overs, BB, Opposition) %>%
  kable(digits = 1)
  
  
```

# Wickets

### Most Wickets (all time)

```{r}
df_all %>%
  arrange(desc(Wkts), Balls) %>%
  select(Name, innings, Overs, Wkts, Runs, Avg, SR) %>%
  filter(row_number(desc(Wkts)) < 6) %>%
  kable(digits = 1)

```


### Most Wickets (season)

```{r}
df_seas %>%
  arrange(desc(Wkts), Balls) %>%
  select(Name, innings, Overs, Wkts, Runs, Avg, SR) %>%
  ungroup() %>%
  filter(row_number(desc(Wkts)) < 6) %>%
  kable(digits = 1)

```


# Economy
### Best Economy Rate (all time, min 10 overs)

```{r}
df_all %>%
  filter(Overs >= 10) %>%
  arrange(Econ, Balls) %>%
  select(Name, innings, Overs, Runs, Econ) %>%
  filter(row_number(Econ) < 6) %>%
  kable(digits = 1)

```

### Best Economy Rate (season, min 5 overs)

```{r}
df_seas %>%
  filter(Overs >= 5) %>%
  arrange(Econ, Overs) %>%
  select(Name, innings, Overs, Runs, Econ) %>%
  ungroup() %>%
  filter(row_number(Econ) < 6) %>%
  kable(digits = 1)
```

### Best Economy Rate (innings, min 2 overs)

```{r}
bowling %>%
  filter(Overs >= 2) %>%
  arrange(Econ, Overs, desc(Wkts)) %>%
  select(date, Bowlers, Overs, Wkts, Runs, Econ, Opposition) %>%
  ungroup() %>%
  filter(row_number(Econ) < 6) %>%
  kable(digits = 1)

```

# SR
### Best Strike Rate (all time, min 10 overs)

```{r}
df_all %>%
  filter(Overs >= 10) %>%
  arrange(SR, Balls) %>%
  select(Name, innings, Overs, Wkts, SR) %>%
  filter(row_number(SR) < 6) %>%
  kable(digits = 1)

```

### Best Strike Rate (season, min 5 overs)

```{r}
df_seas %>%
  filter(Overs >= 5) %>%
  arrange(SR, Overs) %>%
  select(Name, innings, Overs, Wkts, SR) %>%
  ungroup() %>%
  filter(row_number(SR) < 6) %>%
  kable(digits = 1)
```

# Avg

### Best Average (all time, min 10 overs)

```{r}
df_all %>%
  filter(Overs >= 10) %>%
  arrange(Avg, Balls) %>%
  select(Name, innings, Overs, Wkts, Runs, Avg) %>%
  filter(row_number(Avg) < 6) %>%
  kable(digits = 1)

```

### Best Average (season, min 5 overs)

```{r}
df_seas %>%
  filter(Overs >= 5) %>%
  arrange(Avg, Overs) %>%
  select(Name, innings, Overs, Wkts, Runs, Avg) %>%
  ungroup() %>%
  filter(row_number(Avg) < 6) %>%
  kable(digits = 1)
```