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@fentontaylor
Last active October 20, 2019 22:16
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Project Pitch for Terrificus

Fantasy Fortuneteller

Pitch

Win your fantasy league the smart way.

Problem

In fantasy football, it can be difficult to choose what players to include on your roster on a given week. There are so many variables to consider, that it is impossible to keep track of them all in your head. How do you know which quarterback, running back, wide receiver, etc. is likely to earn the most fantasy points in their next matchup?

Solution

Fantasy Fortuneteller will use machine learning to create prediction models for each type of fantasy player to give you a better idea of how many points you can expect your players to earn in their upcoming games. Maybe a typically productive player is going up against a strong defense this week, and therefore likely to earn fewer points, or vice versa! Instead of needing to watch TV, read articles, and scour stats pages, Fantasy Fortuneteller offers a simple way to streamline your decision-making and maximize your chances of winning.

Target Audience

There are over 40 million fantasy football users in the US and Canada. In 2018, the fantasy sports market generated $13.9 billion in revenue. Fantasy Fortuneteller will target North American fantasy football users.

Features

Ruby Gem - Rumale: A machine learning library with multiple algorithms and model testing options

Integrations

API for game stat data: https://fantasysports.yahooapis.com/fantasy/v2/game/nfl https://www.fantasyfootballnerd.com/fantasy-football-api

Additional data for model building: https://www.kaggle.com/maxhorowitz/nflplaybyplay2009to2016/

Oauth authentication: Google, Facebook

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