Why Trust Eye Test Analytics?
Updated: Nov 25, 2021
There are so many sports ratings systems out there and it can be overwhelming and seem impossible to know which ones to trust. So why trust Eye Test Analytics? My rating system is different because I built it using my eyes as my main guideline hence the name “Eye Test” Analytics. No matter how many numbers I crunched and no matter how many years of data I collected if my ratings didn’t match what my eyes told me than I wasn’t satisfied. After almost a decade worth of hard work I have finally created premier collegiate and professional ratings system and I have years of compelling data and evidence to back up my claim.
For example, in three college basketball seasons from 2017-2019 in a test of 980 postseason tournaments mostly played at neutral sites my formula predicted on average a final score within .23 points accuracy of the odds makers. The odds makers however are able to factor in things such as injuries, momentum, and motivation. In those same 980 games the team with the better overall ratings using my formula had a record of 691-287 which is a win % of .707. To put that into context on average the past three seasons only 13% of the over 350 division 1 teams in college basketball finished the season with a win % above .707. In addition to that, my formula predicted a final score within 3 or less points of the actual final score in 215 out of those 980 games. That means 22% or just about 1 out of every 5 games my formula predicts a final score within 1 basketball possession of the actual final score.
In college football over three seasons from 2017-2019 in a test of 114 postseason bowl games mostly played at neutral sites my formula predicted on average a final score within .25 points accuracy of the odds makers. Like basketball the odds makers however are able to factor in things such as injuries, momentum, and motivation (coaches leaving for other jobs, players sitting out for the draft). In a random test of 854 regular season and bowl games played during those same three seasons, the team with the better overall rating using my formula had a record of 616-238 which is a win % of .721. To put that into context on average over the past 4 seasons only 19% of the 130 division 1 teams in college football have finished the season with a win % above .721. In addition to that, my formula predicted a final score within 3 or less points of the actual final score in 128 out of those 854 games. That means 15% or just about 1 out of every 6 games my formula predicts a final score within a field goal of the actual final score.
Initially my focus was just college ratings but as time went on I decided to transition into professional sports using the same methodology as college. Although my sample size of data testing is much smaller my NFL and NBA ratings have produced results that are on par with the level of accuracy of my college ratings.
Now is the time to get on board with Eye Test Analytics and finally be able to have access to accurate reliable sports ratings that you can depend on!