NBA Game Density Simulator APP
Authors: Jose Fernandez
Working with Shiny more than 1 year
Abstract: The goal of this app is to enable users manipulate different aspects related to the game density (frequency of games) in the NBA for both, a selected team and its opponents over the last 3 seasons. Users can manipulate factors such as court advantage, travel stress, time zones crossed, game density index, direction of travel, etc. As all these are factors that can impact the fatigue of the players.
Full Description: Professional sports in America are characterized by dense schedules with teams having to play multiple games every week in different cities. Furthermore, there are many other factors such as late games, frequent travel, crossing different time zones across the country that may affect a team's performance. On top of this, opposing teams are also undergoing the same challenges. Research in the field of Sport Sciences shows the detrimental effect of these factors on games outcomes.
The goal of this app is to provide a platform for coaches to manipulate different game density factors to better understand what type of schedule stress teams are undergoing at different times during the season. This can help coaches plan training and recovery strategies with the aim to maximize player's performance.
In order to do this, the app does not only provide a summary of some of the main metrics in different forms and visualizations, but also a number of inputs (see right sidebar) to allow users to manipulate each potential factor in different ways. Hence the term "simulator".
Some of the technical aspects involved in the design of this app:
- Provides a dynamic map visualization to track pre-game flight paths.
- Uses different options for dinamic tables based on formattable and DT packages
- Several reactive datasets that react to user selections
Keywords: NBA, Basketball, Game Density, Schedule Load, Travel, Load Simulator, Travel Fatigue
Shiny app: https://josedv.shinyapps.io/NBASchedule/
RStudio Cloud: https://rstudio.cloud/project/1058432