---
# freeze: false # commented out after last update
title: "Olympic Medals 2024"
author: "Me"
date: "2024-08-11"
categories: [Data Analytics, Sports]
format:
html:
toc: true
code-tools: true
execute:
warning: false
echo: false
image: "image.jpg"
fig-width: 10
fig-asp: 0.618
out-width: "100%"
fig-align: center
---
```{r}
#| label: setup
# Load libraries for functions to work
library(httr)
library(rvest)
library(tidyverse)
library(magrittr)
library(purrr)
library(janitor)
library(ggrepel)
# Source functions
source("R/functions.R")
# Define plot style
colors <- c("Gold" = "gold", "Silver" = "#C0C0C0", "Bronze" = "#CD7F32")
linecolor <- c("darkorange", "cadetblue")
plot_style <- theme_minimal() +
theme(plot.title = element_text(hjust = 0.5, size = 20, face = "bold"),
panel.grid.minor.x = element_blank(),
strip.text = element_text(size = 20, face = "bold"),
axis.text = element_text(size = 14),
axis.title = element_text(size = 14),
legend.text = element_text(size = 14),
legend.title = element_text(size = 14))
```
### What's in here?
In this post, we'll compare the officially communicated goals that nations are aiming for against the reality of their performance at the Paris 2024 Olympic Games.
Stay tuned and visit daily, as this report will be refreshed every day to keep you informed of the latest updates to the medal table.
*Last and final update (no further updates will be made to this report): `r paste0(format(Sys.time(), format = "%F %R"), "h")`*
### Select your Country
::: panel-tabset
## Spain
🥇 Spain is dreaming big for the Paris 2024 Olympic Games.
🎯 No one is hiding that [the medal target](https://elpais.com/deportes/juegos-olimpicos/2024-07-08/la-delegacion-espanola-para-los-juegos-olimpicos-mas-deportistas-mas-mujeres-y-mas-equipos.html){target="_blank"} is to beat the 22 medals won in Barcelona’s 1992 Olympics, the best Olympic Games of the country's history.
📈 But is Spain on the right track?
```{r}
#| label: load data spain
# Although functions work with more values, I recommend to only load 1 country and 2 years for comparison
selected_year <- c(1992, 2024)
selected_country <- c("Spain")
olympics_medal_table <- scrape_and_clean_olympics_wiki_multiple(selected_year = selected_year, selected_country = selected_country)
```
```{r}
#| label: prepare data spain
olympics_list <- transform_olympics_data_as_list(olympics_medal_table)
```
```{r}
#| label: define plot style spain
linetypes <- setNames(c("dotted", "solid"), selected_year) # use setNames() to enquote numeric values
```
```{r}
#| label: plot running total comparison spain
plot <- plot_olympics_data(olympics_list$olympics_medal_table_summarized_pivoted,
olympics_list$max_days,
selected_country[[1]])
plot +
labs(x = "Day",
y = "Running Total of Medals",
color = "Year") +
scale_x_continuous(breaks = 0 : max(olympics_list$max_days$max_day)) +
scale_color_manual(values = linecolor) +
scale_linetype_manual(values = linetypes, guide = "none") +
plot_style
```
```{r}
#| label: fitted model spain
fitted_model <- add_slope_olympics_data(olympics_list$olympics_medal_table_summarized_pivoted)
```
### Gold, Silver or Bronze?
The current count of silver and bronze medals is higher than in Barcelona, but it's the gold medals that are missing. Can Spain make up for its gold medal shortcomings?
```{r}
#| label: plot running total per medal comparison spain
#| fig-height: 8
plot <- plot_olympics_data_per_medal(olympics_list$olympics_medal_table_summarized,
selected_country[[1]])
plot +
labs(x = "Day",
y = "Running Total of Medals",
linetype = "Year") +
scale_x_continuous(breaks = 0 : max(olympics_list$max_days$max_day)) +
scale_color_manual(values = colors, guide = "none") +
scale_linetype_manual(values = linetypes) +
plot_style
```
## Germany
🥇 Germany hopes to stop the downward trend in the medal table.
🎯 [The official goal](https://www.sueddeutsche.de/sport/olympia-deutschland-medaillenspiegel-ziel-lux.EWYjh2AYTmCducSPwTBPi2){target="_blank"} is to stay in the top 10 like three years ago in Tokyo and to bounce back from that worst result since their reunification.
📈 But is Germany on the right track?
```{r}
#| label: load data germany
# Although functions work with more values, I recommend to only load 1 country and 2 years for comparison
selected_year <- c(2020, 2024)
selected_country <- c("Germany")
olympics_medal_table <- scrape_and_clean_olympics_wiki_multiple(selected_year = selected_year, selected_country = selected_country)
```
```{r}
#| label: prepare data germany
olympics_list <- transform_olympics_data_as_list(olympics_medal_table)
```
```{r}
#| label: define plot style germany
linetypes <- setNames(c("dotted", "solid"), selected_year) # use setNames() to enquote numeric values
```
```{r}
#| label: plot running total comparison germany
plot <- plot_olympics_data(olympics_list$olympics_medal_table_summarized_pivoted,
olympics_list$max_days,
selected_country[[1]])
plot +
labs(x = "Day",
y = "Running Total of Medals",
color = "Year") +
scale_x_continuous(breaks = 0 : max(olympics_list$max_days$max_day)) +
scale_color_manual(values = linecolor) +
scale_linetype_manual(values = linetypes, guide = "none") +
plot_style
```
```{r}
#| label: fitted model germany
fitted_model <- add_slope_olympics_data(olympics_list$olympics_medal_table_summarized_pivoted)
```
### Gold, Silver or Bronze?
While the overall medal target seems far away, with the number of gold medals they've won, Germany is well on their way to matching their last position.
Are they going to reach the 10 times gold from Tokyo?
```{r}
#| label: plot running total per medal comparison germany
#| fig-height: 8
plot <- plot_olympics_data_per_medal(olympics_list$olympics_medal_table_summarized,
selected_country[[1]],
with_labels = FALSE)
plot +
labs(x = "Day",
y = "Running Total of Medals",
linetype = "Year") +
scale_x_continuous(breaks = 0 : max(olympics_list$max_days$max_day)) +
scale_color_manual(values = colors, guide = "none") +
scale_linetype_manual(values = linetypes) +
plot_style
```
## France
🥇 France's Olympic dream is evolving from host to champion.
🎯 [Their medal mission](https://www.lemonde.fr/sport/article/2021/10/14/jo-2024-de-grandes-ambitions-mais-des-petites-foulees-pour-le-sport-francais_6098291_3242.html){target="_blank"}, officially communicated by Emmanuel Macron, is to return to the top 5 as in Atlanta 1996, where they have so far obtained their gold medal record.
📈 But is France on the right track?
```{r}
#| label: load data france
# Although functions work with more values, I recommend to only load 1 country and 2 years for comparison
selected_year <- c(1996, 2024)
selected_country <- c("France")
olympics_medal_table <- scrape_and_clean_olympics_wiki_multiple(selected_year = selected_year, selected_country = selected_country)
```
```{r}
#| label: prepare data france
# Manually fill missing values from Wikipedia table :-(
olympics_medal_table_imputed <- olympics_medal_table %>%
mutate(date_cod =
case_when(
medal == "Gold" &
name == "Christophe CapellePhilippe ErmenaultJean-Michel MoninFrancis Moreau" &
sport == "Cycling" &
event == "Men's team pursuit" ~ as_date("1996-07-27"),
medal == "Gold" &
name == "Nathalie Lancien" &
sport == "Cycling" &
event == "Women's points race" ~ as_date("1996-07-28"),
medal == "Gold" &
name == "Jean-Pierre Amat" &
sport == "Shooting" &
event == "Men's 50 m rifle three positions" ~ as_date("1996-07-27"),
medal == "Silver" &
name == "Philippe Ermenault" &
sport == "Cycling" &
event == "Men's individual pursuit" ~ as_date("1996-07-26"),
medal == "Silver" &
name == "Marion Clignet" &
sport == "Cycling" &
event == "Women's individual pursuit" ~ as_date("1996-07-28"),
medal == "Silver" &
name == "Jeannie Longo" &
sport == "Cycling" &
event == "Women's road time trial" ~ as_date("1996-08-03"),
medal == "Bronze" &
name == "Jean-Pierre Amat" &
sport == "Shooting" &
event == "Men's 10 m air rifle" ~ as_date("1996-07-22"),
.default = date_cod))
olympics_list <- transform_olympics_data_as_list(olympics_medal_table_imputed)
```
```{r}
#| label: define plot style france
linetypes <- setNames(c("dotted", "solid"), selected_year) # use setNames() to enquote numeric values
```
```{r}
#| label: plot running total comparison france
plot <- plot_olympics_data(olympics_list$olympics_medal_table_summarized_pivoted,
olympics_list$max_days,
selected_country[[1]])
plot +
labs(x = "Day",
y = "Running Total of Medals",
color = "Year") +
scale_x_continuous(breaks = 0 : max(olympics_list$max_days$max_day)) +
scale_color_manual(values = linecolor) +
scale_linetype_manual(values = linetypes, guide = "none") +
plot_style
```
```{r}
#| label: fitted model france
fitted_model <- add_slope_olympics_data(olympics_list$olympics_medal_table_summarized_pivoted)
```
### Gold, Silver or Bronze?
The `r selected_year[[1]]` team has set the bar high with `r fitted_model %>% filter(year == selected_year[[1]]) %>% pull(max_running_total_year_country) %>% round(1)` medals, but France already exceeded that number by `r (fitted_model %>% filter(year == selected_year[[2]]) %>% pull(max_running_total_year_country) %>% round(1)) - fitted_model %>% filter(year == selected_year[[1]]) %>% pull(max_running_total_year_country) %>% round(1)`.
Where will their new gold medal record be set?
```{r}
#| label: plot running total per medal comparison france
#| fig-height: 8
plot <- plot_olympics_data_per_medal(olympics_list$olympics_medal_table_summarized,
selected_country[[1]],
with_labels = FALSE)
plot +
labs(x = "Day",
y = "Running Total of Medals",
linetype = "Year") +
scale_x_continuous(breaks = 0 : max(olympics_list$max_days$max_day)) +
scale_color_manual(values = colors, guide = "none") +
scale_linetype_manual(values = linetypes) +
plot_style
```
:::
### References
- Data is downloaded from Wikipedia and is subject to the source being up to date.
- [Olympic Games overview](https://en.wikipedia.org/wiki/List_of_Olympic_Games_host_cities){target="_blank"}.
- Spain: [1992](https://en.wikipedia.org/wiki/Spain_at_the_1992_Summer_Olympics){target="_blank"} and [current performance](https://en.wikipedia.org/wiki/Spain_at_the_2024_Summer_Olympics){target="_blank"}.
- Germany: [2020](https://en.wikipedia.org/wiki/Germany_at_the_2020_Summer_Olympics){target="_blank"} and [current performance](https://en.wikipedia.org/wiki/Germany_at_the_2024_Summer_Olympics){target="_blank"}.
- France: [1996](https://en.wikipedia.org/wiki/France_at_the_1996_Summer_Olympics){target="_blank"} and [current performance](https://en.wikipedia.org/wiki/France_at_the_2024_Summer_Olympics){target="_blank"}.
- Check out my [GitHub repository](https://github.com/dani-f/olympic-medals){target="_blank"} to see how this report was compiled and adapt it to any country.
{width="30%" fig-align="center"}
