Live: http://protopizza.github.io/ApIsOp/
by Kevin Liu (protopizza), So Choi (sos0)
As two avid League of Legends players, finding out that AP itemization was being reworked was a bit of a surprise. Would our favorite AP mage champions still be strong? How would these changes affect the champion spectrum? With these questions in mind, we set out to analyze and display the data handed to us with a single hope in mind: that AP is OP.
We feature three sections using the 5.11 dataset, 5.14 dataset, and some manually collected data regarding NA LCS matches that used 5.11 and 5.14 patches. The 'Champions' tab is an analysis and visualization of champions' item selection between patches. 'Items' tab specifically compares win and buy rates of AP items that were changed in 5.14, and the 'Predictions' tab showcases our machine learning results used to predict which team in the Summer Split matches actually won.
Our methodologies and interesting findings for all sections mentioned above can be found in the 'About' tab of our live site.
Additional Info:
- Front-end libraries/frameworks: d3.js, jQuery, Semantic-UI, and moment.js
- Python + libraries used: requests, scikit-learn, numpy, scipy