How I Used Analytics to Almost Win my Fantasy Football League Last Year
The 2019 NFL season started a few days ago, and along with it started many different types of Fantasy Football leagues. All participants, approximately 50,000,000, recently had their drafts. There are those of us that live and breathe the NFL. Those that can somehow store each team’s schedule, who the first 3 players are at each position on the depth chart, and have the last few years’ worth of data in their own personal database. Others, like yours truly, need more help.
Prior to 2018
Before the draft, fantasy participants log into their favorite sites to download what are known as “Cheat Sheets.” These sheets are players’ rankings for each position, created by any of the numerous sites out there. Similar to a basic Google Search, I personally looked at a few different sites, determined which sites and data sets I would use, and printed their cheat sheets for future reference. In order to have the most up-to-date cheat sheet, I did this fairly close to the draft. I then combined the average position of the players between the 3 or 4 sheets I had along with my limited memory of each player’s performance from last season, and went about drafting my team.
Once your team is created, you wait for the season to start. Post-draft and during the season, participants will try to improve their team from week to week, based on player performance and their players’ opponents.
During the week, I checked out the waiver wire, took a look at who was out there, and compared them to my players to see if there was someone I should pick up. This was purely based on fantasy points, as that was all of the data I sought. Some panned out, some did not. I continued this method throughout the season, until week 13, when the playoffs started and my fantasy season was over. I had fun being a spoiler every once in a while, but I would almost always miss the playoffs.
What I had been doing was what so many people do. I was making decisions based off of reports that were created in the beginning of the week that had been sitting on my desk, not being updated. By the time I went to update my team, e.g. Player Updates and Who to Start, I was using out-of-date information to make current decisions. The pre-draft cheat sheets I used were as current as I could get them, but they were also static, with only a flattened version of player rankings.
The in-season tools I used, provided by my fantasy football platform were not as static. With those, you can sort based on any of the statistics they presented. Once I found this, I had a slightly more success because I changed 1 KPI I had looked at (KPI: Key Performance Indicator). I no longer looked strictly at how many points a player could get the following week, but also how many times that player was added vs dropped. This let me know which payers were hot during the current week.
I was just dipping my toes into some advanced analytics for fantasy football.
2018 – Time for a Change
Last year’s season I decided that I had donated enough money to the others in my league, and therefore wanted to take fantasy football more seriously. If I wanted to do better, I would have to up my game.
This time around, I chose to sign up with a service for the draft. Prior to the draft, I was able to link my league with this service, so that it could calculate my draft position. I would manually mark players taken as the draft went on. This tool would show me the top 4 players to consider based on who was left in the draft and who I already had on my team, updating each time a player was removed from the board. I had to come up with the order in which I wanted to draft players, however this time I had much more, and better, information to make decisions when I went to draft a position. For example, I was able to determine if I was getting a deal on a player because I could draft them above their average position, across all other drafts on the platform.
The result? I received an A+ for my draft and was ranked #1 going into the season. I would never use a paper cheat sheet again.
I decided to sign up with this service for the season. It helped me do well with my draft, so why not give it a try for a year. Because this service was connected to my league, it could better analyze which players would best fit on my team compared to the fantasy platform I was using before. No longer was I just selecting the top player from a list of players ranked after the previous week. I was now able to pick from a few players, any of which would help improve my team, based on advanced logic in the system. I could analyze trade offers more in-depth than just how many points were predicted to accumulate for the rest of the season.
I went from having the best draft pre-season and scoring the most points in the league, to being ranked 1st going into the playoffs and only losing 2 games all season. Other than my superstar QB having an off week, I found myself in the consolation game. The next week, I scored enough points to have easily beaten anyone in the league – this is where the “Almost” you read in this blog’s title comes in. Despite this, I came in 3rd. My highest finish ever.
What I found is that, having better access to the live data, which was presented in a very simple manner, made it easy for me to get the player insights I was looking for. I made enough money in the league to cover my buy in, my service cost and pay for a nice dinner.
Having used the same service this year for my draft, my fantasy service gave me the second highest draft grade in the league. In speaking with others in the league, they all think that I have the best team. That remains to be seen, but having access to this data will absolutely give me a chance.
If changing the way I accessed data, and how that data was analyzed could help me take my team for worst to (almost) first, what could it do for your business?
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