By the Numbers: Preseason Ratings Release
Prep Girls Hoops Minnesota will once again be the home for the most comprehensive rating system for Minnesota girls’ basketball. We rate over 400 teams on a daily basis throughout the season. Although the algorithm is similar, there have been a few upgrades as well as additions to the information we will provide. The ratings can be found at the link below or in the More Content tab above.
How are the Preseason Ratings Determined?
The preseason ratings are found using a simple weighted average. Since I have only been able to backfill the previous two years of data with the updated formulas, those are the only two seasons being used. Therefore, teams that were good for the past two years will be rated highly, regardless of what the expectations are for this season.
What is absent from the preseason ratings is anything to do with individuals. I am unable to input the value of an individual player into the rankings, and unless I quit my day job and require all coaches to send me a box score after each game, I do not plan to. Injuries, transfers, and other effects an individual can have on a team are not included in these rankings. Some teams will be drastically overrated right away, while others will be underrated just as much. As the preseason ratings disappear (after a team plays 8 games), things will begin to work themselves out.
So Who is #1?
The top team in the state in Class AAAA (and overall) is Hopkins. They had one of the more remarkable seasons I can remember last year. Not only did they finish as undefeated state
champions, just one of their 32 wins was a single digit victory. With a still loaded roster, this season has the chance to be just as special.
DeLaSalle is the top team in Class AAA. The Islanders are also coming off a state title and were also state tournament entrants in the previous year. They finished the season with 15 straight victories and look to keep that momentum into this season.
Waseca drops down a class and comes in at #1 in Class AA. Although they have failed to make the Class AAA state tournament the past two years, their record is an impressive 51-7. We’ll see if the change in class sparks the Bluejays back to the state tournament.
Mountain Iron-Buhl holds the top spot in Class A once again. They have been a juggernaut up north for a while now considering the last time they missed the state tournament was in 2010. This season they should continue to be strong but will face some challengers up north.
The Big 9 is Still a Problem to Rate
Even after backfilling the new adjustments to the system for the past two years, the Big 9 is still a difficult conference to rate. Many of the top teams are far underrated. Take Red Wing for example. They finished last season at 24-3 with wins over three teams the system loves (Goodhue, Waseca, and Kasson-Mantorville) in their non-conference portion of the schedule. All of that and they were still only able to muster the #18 ranking in Class AAA. This year, they begin as the #29 ranked team in AAA.
I wrote about this last year, but I still think the main issue is that they play 22 conference games in a 25 or 26 game schedule. That does not allow for a great deal of comparison throughout the rest of the state.
The other problem I see is the struggles that the bottom of the conference has gone through. The bottom five teams in the conference standings last year combined for 19 wins on the season, all of them against each other. The best scoring differential of the group belonged to Owatonna at -16.1 points per game. If the bottom of the conference improves, the ratings of the top teams in the conference should improve as well. Hopefully it all becomes a moot point after the season begins.
Early Season Predictions
This season I will continue to post predictions for each game that I am aware of on Twitter (@MNBBRatings). At the beginning of the year there may be some predictions that do not make sense based on the loss of players due to graduation or the addition of players. The predictions are not me personally predicting those games, it is a computer using the current ratings. If the prediction is way off what is expected (which will certainly happen for a few games), then the result of that game will only help to make the ratings better and future predictions more accurate.