Click the Change Game button to choose a new game to predict.
When you click the Change Game button, a pop-up menu should appear. Use that pop-up menu to select which college football Week 12 game to predict.
The system begins with a random game loaded by default, but you can use the pop-up menu to change that game.
You can also use the drop down menus in the Adjust Lines section to change the selected game's betting lines to match your pick'em contest or preferred sports book.
Adjusting betting lines is an optional step. The values pre-loaded in the drop down menus represent the most recent betting lines we have stored in our system.
Once you have chosen a game to predict and adjusted lines if necessary, move on to Step 2: Choose Predictive Factors.
2. Choose Predictive Factors
| Stat | Importance |
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Click the Edit Stats button to choose the statistics that will drive predictions.
All game predictions are based on the statistical factors you choose, combined with more than five years of historical game results, stats, and betting odds information.
When you click the Edit Stats button, a pop-up menu should appear. Use that pop-up menu to select the stats to use in your customized predictive model.
The system begins with four predictive factors selected by default, but you can use the pop-up menu to change, add to, or delete those stats.
Remember to click the Save Stats button at the bottom of the pop-up menu to save your selected stats.
If you think some of your chosen stats are more important than others, use the sliders to set the relative importance of each predictive factor.
You can use the Save current factors link to save combinations of stats for use in future weeks. You can even save multiple factor sets to track and compare the performance of different predictive strategies.
Once you have selected predictive factors and set their relative importance levels, click the Get Predictions button to generate predictions.
Your Predictions
This table presents your model's game predictions, based on current information and betting odds.
The system uses an objective, 100% data-driven method to predict the percentage odds of each team winning the game and covering the selected point spread.
Similarly, it computes the percentage odds that the total number of points scored in the game will be over or under the selected totals line.
Money Line Value indicates whether each teamÕs win odds, according to your model's predictions, are higher than the win odds implied by its money line odds. If this is not the case for either team, there will be no Money Line Value pick.
Important note: Positive Money Line Value does not imply a high-percentage winning bet. A long shot money line bet can have relative value, but it still will lose far more often than it wins.
The Most Likely Final Score prediction is included mostly for fun. It's extremely difficult to predict final scores with a high degree of accuracy, and we've only just begun to explore this challenge.
However, note that it is mathematically feasible for the Most Likely Final Score to apparently "contradict" other predictions. For instance, it's perfectly logical to have a Most Likely Final Score of 21-17 in favor of Team A (let's say there's an 8% chance of that final score), but your model still favors Team B to cover a spread of +3 (55% chance).
Remember that your model only incorporates your selected predictive factors. You must make subjective adjustments to predictions to account for any recent player injuries or other information that may significantly affect a team's performance.
As always, please don't hesitate to contact us if you have a question or notice something that doesn't seem to work properly.