The shot chart application features 2 primary chart types (heat maps and marker charts), and filters for selecting different players, teams, or individual games. Hovering over the heat maps will display a player's (or team's) ranking in that particular zone, along with their make / miss splits and shooting percentages, as well as the league's make / miss splits and shooting percentages.


The style of these charts is highly motivated from similar shot charts created by Kirk Goldsberry.


Tip: to avoid excessive scrolling, hit backspace to clear the name and then type the player/team whose graph you'd like to see. Use arrow keys or enter to auto-complete.




Author
Nicholas Canova


The player comparison application is a scatter plotting tool that creates marker graphs based on the chart type selected. Markers can be filtered by position to get a better sense for which players perform best at their positions. Additionally, player and team inputs can be selected to emphasize the selected player / the players on the selected team. I am working on a filter that will allow users to set their own minutes-played threshold for determining which players qualify for the chart


Hovering over the individual markers on the scatter plots reveals who that player is, as well as the player's statistics for the graph.




Author
Nicholas Canova


The team comparison application is a scatter plotting tool that creates logo graphs based on the chart type selected - it features 5 primary chart types, as well as the ability to create your own chart by selecting the team statistics to plot on the X and Y axes.


If the create-your-own-chart functionality is well received, I will add this into the player comparision application. I may also build additional preset charts.




Author
Nicholas Canova


The game recap application features an in game win probability (IGWP) line graph as well as a leads bar plot. Hovering over the IGWP graph shows the score of the game at that moment, as well as each team's win probability. Computing a decent estimate for IGWP is actually fairly simple, requiring only the current score, number of minutes remaining, and the pregame strength of each team.


I am working on additional effects for this tool




Author
Nicholas Canova





The ELO Ratings application creates line graphs that highlight each team's historical ELO rating (over the last 5 years), with markers displaying the team's highest and lowest rating over this period. This application was motivated 100% by an identical application built by FiveThirtyEight - here.


In an effort to improve my sports data vis skills, I attempted to reproduce their application to the best of my ability, although my graphs lagged quite a bit with >5 years displayed.




Author
Nicholas Canova


The assist networks application is a network graphing tool that displays which players on each team are assisting their teammates most frequently. A filter is provided for the number of nodes to include in the network graph, as well as a player on the selected team to highlight.


Similar to the ELO Ratings chart, this is not an original idea of mine. Motivations for these graphs come from PResidual and CrumpledJumper




Author
Nicholas Canova



The four factors application is a bar graphing tool that displays Dean Oliver's Four Factors of Basketball Success. The radio buttons toggle between two charts with a similar layout, but with different information shown


Hovering over the individuals bars reveals each team's stat value, as well as the team's ranking, for that factor.




Author
Nicholas Canova

The player percentiles application is a box and scatter plotting tool that displays the percentile rankings of players across 11 different stats. Each marker can be hovered over to see that player and his statistics.


Tip: Use the vertical zoom to better examine the box plots for steal and block percentage.




Author
Nicholas Canova


The outstanding performances application is a bubble-histogram graphing tool, motivated by graphs of a similar style created by both CrumpledJumper and FiveThirtyEight.


Each player's average statistics in the table reflect that player's statistics in only those games where they met the particular stat requirement that is being filtered on.




Author
Nicholas Canova