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 |
The aggregate really likes three games. Florida State over Georgia Tech, SMU over Nevada, and Hawaii over Delaware State. In each of these cases the Aggregate sees the favorite as having a 100% chance to win. It is very early so that data can be unreliable, but the Aggregate is using three different preseason evaluation tools to get those results. The Aggregate is betting on one of those games. It is just the Florida State game. That games odds are the best this week and we are anticipating about a 19% ROI. All of our data points to their victory. The Aggregate would have bet the SMU game, but the ROI basically came out to 0% for the level of investment that we are inputting. We would also have bet on the Hawaii game, but there is no moneyline available for that game. The Aggregate did invest in a 2 pick parlay with Florida State and SMU moneyline picks. We are anticipating a 23%ROI for this bet.
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The one game that the Aggregate did not touch is the Montana State, New Mexico game. There are many reasons for this. First, our point calculator, which is a mean based predictor, predicted that Montana State would win the game while our Chance to win calculator, which is a median based predictor, holds that New Mexico will win the game. Second, as we said before this data is pretty small and we are unsure of it's ability to accurately predict anything yet. A couple of our models really like New Mexico's coaching hires and that has given them an edge that they may not actually have especially considering it's their first game. Third, we do not have a good system yet for evaluating FCS schools. Although we have made strides to correct this we still are not able to track all FCS schools and their results and as a result their ratings are based off of an amalgamation of indicators, but not their actual results or off season moves.
