---
title: "Animating Tracking Data"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{animating-tracking-data}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r vignette-options, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "animating-tracking-data-",
  out.width = "100%",
  dpi = 600
)
options(rmarkdown.html_vignette.check_title = FALSE)
```

For the following vignette, you'll need the `sportyR`, `ggplot2`, and `gganimate` packages loaded into your workspace.

```{r setup}
library(sportyR)
library(ggplot2)
library(gganimate)
```

If this is your first experience with plotting tracking data, please check out the [plotting-tracking-data](plotting-tracking-data.html) vignette. Otherwise, let's see how to make GIFs with `sportyR` and `gganimate`.

## The Data

For this example, we'll use a play from Week 15 of the 2018 NFL season between the Chicago Bears and Green Bay Packers. Data made available for the [Big Data Bowl 2021](https://www.kaggle.com/c/nfl-big-data-bowl-2021) Kaggle competition.

```{r bdb-example-read-data}
# Load the play data
example_nfl_play <- data.table::fread(
  glue::glue(
    "https://raw.githubusercontent.com/sportsdataverse/sportyR/",
    "main/data-raw/example-pbp-data.csv"
  )
)

# Convert to data frame
example_nfl_play <- as.data.frame(example_nfl_play)
```

To keep things easy, let's specify the colors for each team's dots on the resulting GIF. We'll make the Bears [orange]{style="color: #c83803"} and the Packers [yellow]{style="color: #ffb612"}. The football will also need a dot to be seen; let's make it [brown]{style="color: #624a2e"}.

```{r bdb-example-prep-data}
# Prep data for plotting
example_nfl_play[example_nfl_play["team"] == "home", "color"] <- "#c83803"
example_nfl_play[example_nfl_play["team"] == "away", "color"] <- "#ffb612"
example_nfl_play[example_nfl_play["team"] == "football", "color"] <- "#624a2e"
```

First, let's draw an NFL field via `geom_football("nfl")`. We'll adjust the origin to be in the lower left corner of the field, as per the notes on the coordinate system on the Kaggle page describing the data.

```{r bdb-example-draw-field, eval = FALSE}
# Create the field
nfl_field <- geom_football("nfl", x_trans = 60, y_trans = 26.6667)

# Display the field
nfl_field
```
![Image of NFL field rendered from sportyR](https://raw.githubusercontent.com/sportsdataverse/sportyR/main/vignettes/img/animating-tracking-data-bdb-example-draw-field.png){width=75%}

Looks good! Now, let's animate using `gganimate`.

```{r bdb-example-animate-play, eval = FALSE}
# Add the points on the field
play_anim <- nfl_field +
  geom_point(
    data = example_nfl_play,
    aes(x, y),
    color = example_nfl_play$color
  ) +
  transition_time(example_nfl_play$frameId)

# Show the animation
play_anim
```
![Gif of tracking data](https://raw.githubusercontent.com/sportsdataverse/sportyR/main/vignettes/img/animating-tracking-data-bdb-example-animate-play.gif){width=75%}

Easy peasy. As noted on the [plotting-tracking-data](plotting-tracking-data.html) vignette, this too works so long as the geospatial data is provided and contains a way to identify and order the frames of the resulting GIF.