Canadian Curling Scrapper

Over the past few decades, data analytics have become more and more present and important in professional sport. This software's aim is to open up those possibilities to the world of professional Curling in Canada.

Compiling data from Curling Canada's database, the software allows users to customize their data set by selecting different attributes from the game, such as player shot percentages, line scores, final scores, time remaining, and hammer possessions. These attributes can be combined using mathematical and logical functions, allowing for almost limitless analysis opportunities.

Once a data set has been created, it is cleaned and exported as a CSV file.

Current work is being done to give users the ability to customize neural network models that can be trained on the same custom data sets.

Sasaktoon Transit Research

Co-authors: Lukas Cowan, Jordan Jungwirth

In our Total Quality Management class at the Edward's School of Business, we were assigned a project to choose a company in Saskatoon and research their processes. Being university students who used public transport almost daily, we decided to research the Saskatoon Transit's bus system, focusing on route 17 Stonebridge-University.

Using reports provided to us by Saskatoon Transit, interviews with Saskatoon Transit, and stop data obtained through Saskatoon Transit's public GTFS Realtime application programming interface (API). We investigated the bus system's efficiency based on how late or early busses arrived based on their scheduled arrival time (ie. timeliness).

We found that Saskatoon Transit's timeliness was highly varied, however, we could not wholly attribute periods when busses were running late or early to any particular stop or time of day because the spikes (either early or late) didn't always correspond with periods of high traffic or after specific stops. Our principal recommendation is that data be collected whenever busses pass a stop in addition to physically stopping. This will lead to a more consistent data set and would lead to more definitive findings.

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