Because there is only so much that I can rabble on without backing up my words, I’m going to base our writeup on these 3 charts you see above. These charts are stats from the season champions after week 1.

The champs from each season are:

2012 – D Smith

2013 – Jake

2014 – Nic

2015 – Val

2016 – Matt

2017 – Nic

2018 – Jake

2019 – Nic

2020 – Alex

So that’s 9 years of history still existing in our system (we have a handful of years that were in a separate league that are missing and I do not know how to find). Sample size is relatively small for that reason, but we work with what we have.

Did they win week 1?

The champ tends to win week 1, but it is not a conclusive difference. I suspect it would be 50/50 if there were an even amount of years drawn on here. But for the sake of my point here, we would like a winner.

Winners in week 1: Cone, Alex, Matt, Pender, Jake, and Andrew.

Points for:

This is their standings in points for after week 1. 1^st means they scored the most points in the league, 12^th means they scored the least. 11^th, 1^st, and 4^th are the positions that jump out right away as the only ranks that have been represented twice. 2^nd, 3^rd, and 8^th have each been represented once. 5^th, 6^th, 7^th, 9^th, 10^th, and 12^th have never won. Are they due? Is their statistical significance to these spots? Can I create bias by telling you what this means relative to you? I’m gonna give it a shot at least.

Points for standings

Cone
Pender
Jake
Alex
Matt
Ory
Andrew
Val
D Smith
Nic
Gary
Yuriy

Above you can see the bolded names as the most likely to win given points for statistics. Italicized for least likely to win, and those without any fancy typography right in the middle.

Points Against:

Points against is almost a measure of luck. What can you do to stop the opposing team from scoring points? Apparently a lot, as we can see there is a significant number here. So before we get to that, I’ll explain this chart a bit more. 12^th place is the person with the least amount of points scored against them. 1^st place is the person with the most amount of points scored against them. This is only after the first game. 10^th place is a sweet spot. 3 out of 9 means 33% of the time the person that wins goes against the 10^th highest scoring team in week 1. But even more predictive is that only two teams went against a top-half scoring team in the first week. 2 out of 9. Is that luck in number form? Is this statistic just noise? Let’s see.

Points against rankings current:

Val
Yuriy
D Smith
Nic
Ory
Matt
Gary
Cone
Jake
Alex
Andrew
Pender

Bolded are the two most likely to win based on the data. Italicized are the least likely to win based on the data. Non-stylized typography are those that have won before but are not represented strongly. Can different numbers break through? Is this a pattern or is it all just random? Something interesting about this data is the teams that won with a 1^st and 2^nd place points against are both recent winners (last 4 years), which could potentially be a function of decimal scoring or stronger passing. Potentially, if I knew exactly what this all meant I would be getting paid for it.

WHO ARE THE MOST LIKELY TO WIN:

Based on the data here, the most likely to win is none other than Alex. That’s right, the dumb data here is predicting a repeat. I am no longer a fan of this method, but we will continue down the rabbit hole.