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The Aggregate is a formula I devised to help predict future outcomes for games. It is based on three factors: point differential, opponent strength, and game locations. As a predictor it was accurate 72.9% of the time last season (216 games) All rights to this formula and contents here within are owned by me. As an Amazon Associate I earn from qualifying purchases.
Sunday, August 25, 2024
Week 0 Betting Summary
Saturday, August 24, 2024
Week 0 Aggregate CFB Picks
College football is finally back and the Aggregate has predicted the first four games. Some special notes out here before you begin using the Aggregate predictor as a betting guide.
One, the aggregate was effective last year and correctly selected almost 79% of winners during the regular season college football games. That sample size was about 170 games. This is likely too small a sample size to prove the aggregates ability. Personally I do believe in the data and am wagering this year based on that research, but you should know the wagers are very small. With the development of more automation in my process I should have a much larger sample size to work with after this season. However, whatever advice we may give is all at your own discretion. Your decisions are you own. I do promise to be honest about the Aggregates winning and losing and all of the data so that you can see what is working and what is not.
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Two, the Aggregate was unable to accurately predict against the spread or over/under last year. Officially the Aggregate was 12 games under .500 against the spread and 3 games under against the over/under. Both of these percentages would only have lost money last year and I do not plan on betting any money on these categories although we will still list that information. I have made some small changes where those formulas are concerned including now factoring standard deviation to those calculations and am hopeful to get better results this season. I will continue to track how the formula does.
Three, the Aggregate betting system will work this way. Because of my extremely small bank roll I will be betting on approximately 14 games a week with the exception of Week 0 and 1 which will be a combined 14. For me these 14 games will be chosen by whichever teams have the best chance to win. The goal is to win as many as possible and if we are winning 79 percent than we will be making money. The actual percentage should be much higher as the 79 percent was based on all games even games where the favorite my only be favored by a percent or two.
Four, other than the 14 moneyline bets I will place one bet per week on a parlay. Parlay's are notoriously tricky, but are very lucrative. This parlay will always just include moneyline bets as that's the category where the Aggregate has done so well in. The method behind picking those games will be simple. Any game where the Aggregate see's a 90% chance for a team to win or better will be included in the parlay for that week. The reason behind this is because last spring when the Aggregate broke down the NCAA basketball tournament it never failed to correctly predict a winner when the chance to win was 90% or higher. This is also a very small sample size and not one specifically from college football. I do not have the data for this for college football last year as I wasn't tracking it yet, but we'll have more data on this after this year. You should know that in the NCAA tournament only 9 games out of 65 met this criteria so the likelihood of many games with this are small. If for some reason there are not multiple games that meet this criteria than we will not place a parlay bet.
Five, although we will be betting the same amount each week it would be smart to only bet small amounts early on. The reason for this is simple. At the beginning of the season we don't have very much data. The Aggregates preseason projections are based off of last year's teams rating, players lost and gained, and coaches lost and gained. This is our first year coming up with a preseason rating so it is very new and has no proven data. Because of this I weighed also Phil Steele's best power rating into the calculation so as to mitigate any outliers. As we gain more data about this I will move away from this. As we move further into the season though teams will show us who is best and who we can trust based on their results. This is the surest way to feel confident in betting with the Aggregate.
So now that you have been forewarned here is the Aggregate's Week 0 predictions:
Week Zero CFB Predictions | ||||||
Teams | Record | Score Prediction | Chance to Win | Vegas Line | O/U | Moneyline |
Saturday, August 24th | ||||||
#10 Florida State | 0-0 | 38 | 100.0% | -10.5 | 55.5 | -$450.00 |
Georgia Tech | 0-0 | 24 | 0.0% | $360.00 | ||
Montana State | 0-0 | 46 | 33.0% | -13.5 | 54.5 | -$550.00 |
New Mexico | 0-0 | 44 | 66.7% | $425.00 | ||
SMU | 0-0 | 42 | 100.0% | -27.0 | 55.5 | -$3,500.00 |
Nevada | 0-0 | 13 | 0.0% | $1,500.00 | ||
Sunday, August 25th | ||||||
Deleware State | 0-0 | 21 | 0.00% | N/A | ||
Hawaii | 0-0 | 35 | 100.00% | -40.5 | 55.5 | N/A |
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Thursday, August 1, 2024
Mountain West Coaches Adjusted Winning Percentage

I've often felt that winning percentage is not a great look at how good coaches actually perform as it does not factor in a multitude of items including environment, player talent and competition. As a result I devised a formula to try and tackle some of that problem and give a more accurate portrayal of what part of the wins and losses the head coach was responsible for.
This metric, the adjusted win percentage for FBS coaches, tries to take into account at least the players that each coach is responsible for. For example when a new head coach wins in their very first year the credit only lies somewhat with them. Many of the players they are winning with were recruited by the previous staff. Often these coaches go on to not be successful in the long term. The best examples I can think of are Ed Orgeron at LSU or Gene Chizik at Auburn. Both should be noted actually had their best year a few years in, but neither lasted after a prolonged time. On the flip side new coaches often lose heavily in their first year because it takes time to recruit and install new systems and to get a full buy-in from players. Think Sabin's first year at Alabama or Bobby Petrino's first at Arkansas.
The basic thrust of the formula is this, the longer a coach has coached a team the more accountable he is for their wins and losses. The transfer portal has changed some of this in that the formula now holds coaches more accountable sooner. Gone are the days when you had four years to show some results.
Special notes, these statistics are based on fbs wins and losses only. The time period for the coaches is endless so all the coaches years are included, but it is only an evaluation of current coaches not coaches from the past.
With all that said here is the fourth in the series, the Mountain West conference. You will notice that this includes only teams eligible for the Mountain West Championship game. Despite playing six games against Mountain West teams this year neither Oregon State nor Washington State are eligible in the Mountain West standings at the time of this posting.
Biggest thing that stands out about the Mountain West is their lack of under .500 coaches. They have only two. Compared to the conferences I've evaluated so far that is extremely low. The next closest conference to that was Conference USA with six.
What does that mean for the Mountain West? Mostly I think it means they have a lot of retread coaches. There are three coaches in the Mountain West with 100 plus adjusted wins. None of the conferences I have evaluated so far have had any. Seven Mountain West coaches had previous coaching stops as head coaches and then there is Troy Calhoun who has been at Air Force since 2007.
So who is the Coach with the best adjusted win percentage in the Mountain West? Well it's Spencer Danielson although the adjusted winning percentage only gives him credit for .75 wins and .25 losses. In other words they went 3-1 when he took over last year, but since he took over at the end of the season the adjusted winning percentage only gives him credit for 25% of the wins and losses. We'll get a better idea of how good he is after this season.
Behind him is Bronco Mendenhall with a career adjusted winning percentage of 64.7%. You've got to feel good if you're a Lobos fan right now. You just hired a coach with a very good winning pedigree.
Note: Jay Sawvel and Jeff Choate have no wins or losses as an FBS coach which is why they're an incomplete here.
MW Coaches | Team | W | L | W Pct |
Jay Sawvel | Wyoming | 0.0 | 0.0 | #DIV/0! |
Jeff Choate | Nevada | 0.0 | 0.0 | #DIV/0! |
Spencer Danielson | Boise State | 0.8 | 0.3 | 75.0% |
Bronco Mendenhall | New Mexico | 115.3 | 62.8 | 64.7% |
Troy Calhoun | Air Force | 117.3 | 75.3 | 60.9% |
Jeff Tedford | Fresno State | 101.8 | 67.8 | 60.0% |
Ken Niumatalolo | San Jose State | 95.8 | 75.4 | 56.0% |
Blake Anderson | Utah State | 56.8 | 44.8 | 55.9% |
Barry Odom | UNLV | 21.0 | 17.3 | 54.9% |
Jay Norvell | Colorado State | 33.3 | 28.3 | 54.1% |
Sean Lewis | San Diego State | 20.8 | 22.0 | 48.5% |
Timmy Chang | Hawai'i | 6.5 | 13.0 | 33.3% |
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Wednesday, January 17, 2024
End of Year Rankings for Mountain West
SEC End of Season Rankings
The end of year rankings for the 2024 SEC season. The SEC had more parody than ever in the conference and without a dominant team at the t...

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The end of the year rankings are here. The Mountain West finished as the Aggregates 8th best conference this season. The biggest change to ...
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Top 25 for Week 13. The Aggregate has no changes at the top leaving the first five spots untouched. Biggest mover this week was Tulane who...
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Top 25 rankings for week six from the Aggregate. There is a new number one team. Tennessee takes the top spot from Texas after the Longhor...
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Champ Week Rankings for the Aggregate. The Aggregate has dropped all non power four teams ou...
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The end of the year Aggregate rankings for the Big 12 are out. The conference experienced movement in the middle of the rankings after the ...