By Wednesday the Fantasypros rankings were updated, so I went to work on building my database. I built the different React components, set my app up so it would pull the entire database of players when a user reaches the homepage and render players on either side of the trade based on user input. I was lucky that I had built an NBA player database for a previous project, so I was able to utilize that database to supply data to my front-end before I created my NFL player database. I decided to spend the first half of the week building out the front end. As a result, there were no updated rankings available for me to use. I started work on my project on a Monday, where the NFL week was not quite over. This resulted in the first ranked player being assigned a value of 15.00 and the 300th ranked player being assigned a value of 0.05. I wanted to ensure that my application would include enough players to account for leagues of nearly all shapes and sizes, so I chose to include the top 300 players in my formula. The average Fantasy Football league is 12 teams with 16 players on each roster. I decided to develop a formula that would create a numerical rating for each player, allowing for an easier to understand rating for each side of the trade. The formula I developed utilizing Fantasypros rankings However, this rank alone would not be enough for the uses of my project, as it would be hard to combine ranks of many players in an easy to digest way. Fantasypros collects Rest of Season rankings from a variety of Fantasy Football experts and develops a consensus rank for NFL players. I decided that a good rankings base would be Fantasypros’ Rest of Season rankings. I had seen other Trade Analyzers simply using a players average fantasy points per game, but I didn’t feel that this was a good indicator of a players trade value as when you trade for a player it is not their past production that you are trading for, but their future production. One of my initial decisions to make was how I was going to assign value to players. I built the front-end of my project using Class-Based React, and the back-end using Express.js, Node.js and MongoDB. I created this project hoping that I and many others would be able to make use of it throughout each Fantasy Football season. I have been an avid Fantasy Football player for years, and in my search for more resources to utilize I found a few Trade Analyzer’s but they were all either out of date, hard to use or behind a paywall.
#FANTASY FOOTBALL TRADE CALCULATOR SOFTWARE#
A screenshot from my Fantasy Football Trade Analyzerįor my most recent project I decided to combine two of my favorite subjects: Software Engineering and Fantasy Football, to create a Fantasy Football Trade Analyzer application.