echosport

_ what it does _

echosport is a web application powered by Astuce Media, where the user can filter the database of NBA players by multiple columns. Upon clicking on the plus button on the right-hand side, the tuple expands down and the user can see the Basketball player, his stats per game and stats per season, updated in real time.

_ how we built it _

we initially started building echosport on Python (using flask and plotly) on the back-end and React on the front-end. Upon realizing how simple it was to build using React and the plethora of libraries to use, we decided to scrap Python and utilize two libraries in React: React Table & Recharts. The main use-case for this application is to allow first timers and passionate fantasy sport managers to help cultivate the best combination of players possible.

_ challenges we ran into _

Our biggest challenge was utilizing the Astuce Media API queries to fit into what we thought would be a mechanical application. However, upon further inspection, we decided to fetch the first 500 players with their statistics to feed into React Table and then upon clicking each row we parse the necessary data to feed into our Rechart graphs! Another challenge we ran into was taking our time to debug the modules for each team member's laptop, which took hours to debug. Once we settled on React, however, things went smoothly from there.

_ accomplishes that we're proud of _

We are genuinely proud of the hard work we put in. From spending countless time querying the data, to getting all of our branches even with each other, to learning React from scratch; it's safe to say that we had a kick-ass time and our web application looks absolutely beautiful.

_ what we learned _

React (with the many libraries it offers), Bootstrap, Flask and the Astuce Media API!

_ what's next for echosport _

  • Display a more robust user interface for avid fantasy team managers to help select their best players
  • Suggestions from AI to improve team based on machine learning algorithms to implement better and more balanced team with regards to statistics
  • Display player stats in other sports (Baseball, Hockey, Football)
  • Display team stats in basketball and other sports. It will apply machine learning.

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