Toronto Raptors 2019-2020 Atlas

Atlas Web App Link

Geovisualization Project, @RyersonGeo, SA8905, Fall 2020

By Nicolas Karwowski,


Sports have always been a common ground that brings together people of different ethnic and cultural backgrounds. However, regardless of the sport at hand, issues of racism have always accompanied athletic competition. With the reignition of the Black Lives Matter movement in 2020, sports teams and their players had the chance to take a stand against racism in a bigger way than ever before. In my household, we’ve followed the Toronto Raptors basketball team for many years. With this following, we have come to learn the stories of not only our own team’s players but also those of their competitors. I can reliably say that I have spent many hours learning about the hardships and the achievements of athletes from across the globe. While I do not regret spending so much time learning about the diversity of this sport, I understand that others may not have this time. This is why I have chosen to create a geovisualization that represents the complexity of an athlete’s journey to the top and the diversity of my favourite televised sport.


# 7 – Kyle Lowry’s Wikipedia Summary

Thankfully most widely known athletes have easily available information about their journey to the NBA. This usually includes the place they were born, the various schools they attended to hone their skills, and the professional teams they may have played for before reaching the big league. While in-depth bios exist for each team’s core roster on, Wikipedia gives concise summaries of player’s geographic movements throughout their lives. As seen on the right, these summaries can include the player’s date of birth, place of birth, the high schools they attended and their respective locations, the college(s) they attended as well as NBA and other professional teams they might have played on. This information would be vital in the creation of points summarizing the player’s journey to athletic stardom. The main limitation of this information source is that like with other Wikipedia pages, the information could be incorrectly added, sometimes with malicious intent. Lesser known players may also have missing information. Since some players had up to 10 different locations credited in their summaries, I chose to include only ten players from the Raptor’s championship-winning 2019-2020 roster. The mention of the roster’s season is of importance as players come and go as the years go on.


For each player in the visualization, I created a new point feature class in ArcGIS Pro. I entered the points in chronological order so that when I had to connect them later with arrows, the arrows would indicate their path from place to place. Due to the number of points, their accuracy was usually only tied to the listed city’s geographical location. With all the feature classes created, I then added a few new attribute columns so that points in the final visualization could include context.

These attributes included the name of the city, the name of the country the city was located in, the type of location with regards to the player’s life (Place of Birth, School, Professional Team, NBA Team) and the player associated with that point. With this completed, I could link each of the points within feature classes using the Points To Line tool in ArcGIS. The subsequent use of the Split Line at Vertice tools was then done so that arrows could be created between points and not just at the end of the line. Using the Feature Class to Shapefile tool, I was able to export all 20 of the shapefiles, half of which were points and the other half being lines, to ArcGIS Online.

While ArcGIS Online lacks much of the symbology customization available in the desktop version, I made do with a set of simple icons. A green circle would represent the player’s place of birth, schools would be shown as blue diamonds, orange squares symbolized professional basketball and purple stars depicted NBA teams. This type of symbology allows users to understand a player’s journey to the NBA including their ups and downs.

In the final geovisualization web app, users have the ability to customize the map to whatever level they would like. If a user wishes to see where all players are born, they have the ability to turn off all layers except for the Place Of Birth layer. Clicking on any of the remaining green circles creates a pop-up that gives details on what city is there, who is born there and when they were born (as seen above). Alternatively, any and all player layers can be hidden if a user would like to focus on a single-player (as seen below).

Future work

The project as it stands only encapsulates a minuscule sample of all athletes in the NBA. Ideally, this geovisualization would enable to not only view all the Toronto Raptors players but all the players that have ever played in the NBA. When envisioning the perfect visualization, I imagine a crowdsourced app that allows anybody to add their favourite players to the app. Unfortunately, this app is non-editable and many of the steps involved required non-user-friendly applications. This visualization is also deeply limited by ArcGIS Online’s lack of symbology and UI options. These limitations include but are not limited to a search option for the layers manager as well as a grouping option for the symbology tab. Additionally, it would be very interesting to add a timeline feature in the app which allows people to see how the world of basketball has changed over the last few decades in a geographical sense.