NFL 2015 Week 1 Predictions
With the first NFL game of the 2015 season less than 48 hours away, here are the Week 1 game predictions.
For those just joining, Amos is a statistical model created to predict the outcomes of each of NFL game. Amos currently predicts games straight-up. Additionally, Amos then predicts the remainder of the season to compute the ending record of each team.
Amos also has peers within the NFL prediction field. While there are a number of sources for game predictions, I have identified Microsoft’s Bing Prediction and ESPN’s Football Power Index (FPI) as benchmarks for comparison to Amos. Microsoft’s Bing Prediction was previously Microsoft’s Cortana, which was compared to the Bischoff model last NFL season. ESPN’s FPI is new to these comparisons.
First, before the predictions are displayed, it is important to note that predicting the first week within the NFL is a wildcard as only scarce or previous season’s data exists to feed into the model.
A few observations between the models are the confidence varies between them. The highest confidence of Amos is Green Bay over Chicago (94.9%); Bing is also Green Bay over Chicago (71.6%); the FPI is New England over Pittsburgh (67.2%). Amos appears to use the most confidence with its projections, however this also could stem from Amos’ heavy reliance on previous season data to power its model in Week 1.
There are also a lot of agreements among the models, including wins of New England, Green Bay, Denver and Dallas. Most of these are to be expected and should not come as a surprise. However, there are key differences within Week 1.
Deviating from Bing and the FPI, Amos is favoring Cleveland over the NY Jets (64.3%), Buffalo over Indianapolis (58.4%), Detroit over San Diego (65.6%) and Kansas City over Houston (50.0%). Specifically, Kansas City is being favored by just a hair, (approximately less than .02%). Bing deviates from Amos and the FPI with a prediction of Atlanta over Philadelphia (52.0%). The FPI does not disagree with both Amos and Bing in any one specific prediction.
What’s important to note about deviations from the two other models is that they indicate an opportunity for the deviating model to pull away from the other two models as more predictions are correct. Adversely, as deviating predictions do not come to fruition, the deviating model can lag behind the other two models.
Finally, Amos has simulated the entire regular season on available preliminary data. These predictions are expected to change as we move through the season and Amos interprets game outcomes week by week on team’s ending record.
Week 2: 9-7
Week 3: 11-5
Week 4: 9-6
Week 5: 10-4
Week 6: 10-4
Week 7: 9-5
Week 8: 10-4
Week 9: 7-6
Week 11: 10-4
Week 12: 9-7
Week 13: 11-5
Week 14: 9-7
Week 15: 14-2
Week 16: 7-9
Week 17: 9-7
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