Let’s\u00a0make some picks! But let’s make some smart, numbers-based picks…<\/p>\n
Previously, I introduced P2PY methodology to correlate game outcomes (HERE<\/a>). I went through the 2015 bowl season and using year-long P2PY retroactively picked the winner in 28 out of 40 games correctly. This work is currently unpublished but may be subject to a future post. Going forward every week in 2016, I will pick 10 games with a focus on the bigger games for any given week, i.e. those involving ranked teams. For Week 3, I\u2019ve thrown out games against FCS teams (NDSU<\/strong> versus Iowa<\/strong>) or those where a team has only played one game so far (Stanford<\/strong>, Michigan State<\/strong>).<\/p>\n As described earlier, P2PY is meant to be a simple method to estimate a team\u2019s productivity and efficiency. Now, we\u2019re taking it forward to project a team\u2019s score given their opponents defensive performance. The calculation for that is:<\/p>\n TEAM SCORE = SQUARE ROOT (TEAM P2PY * OPPONENTS YARDS AGAINST)<\/p>\n The P2PY is adjusted for schedule. To do this, I used the conference comparisons from colleyrankings.com (HERE<\/a>) that provides each conference with a rating. For example, this week, the Big Ten<\/strong> has the highest rating (0.670349) and the MAC<\/strong> is 0.383017. The data is normalized\u00a0so that the Big Ten was 1 and all others were a percentage of that. A team\u2019s actual P2PY for a week was then multiplied by their opponent\u2019s conference rating to get the adjusted P2PY.<\/p>\n One note, FCS had a rating of 0.130749 which leads to a huge penalty for teams that played FCS opponents. To lessen this penalty, I adjusted this to 0.25, normalized to 0.373. This means that if an offense had an actual P2PY of 3.42 (42 points on 511 yards) but played an FCS team, this gets adjusted to a P2PY of 1.29. This example is for Houston<\/strong> playing Lamar<\/strong> in week 2.<\/p>\n In future weeks, I will likely adjust the defensive yards against in a similar fashion but for week 3, yards against are simply the average of a team\u2019s previous games.<\/p>\n For all calculations, Weeks 1 and 2 are receiving equal weight.<\/p>\n A summary of all of the picks \u2013 straight up and against the spread are below.<\/p>\n Houston @\u00a0Cincinnati (+7) Florida St. @\u00a0Louisville (+2.5) Miami (FL) @ Appalachian St. (+3) Alabama @ Mississippi (+9.5) Oregon @ Nebraska (-3) Texas A&M @ Auburn (-4) Georgia @ Missouri (+6.5) Ohio St. @ Oklahoma (+2.5) 42 22 Ohio St. Ohio St. Temple @ Penn State (-9) 20 25 Penn State Temple Baylor @ Rice (+30) 36 11 Baylor Rice Houston and Cincinnati<\/strong> seems too close for me. I actually like the Cougars a lot more in this game than the prediction would indicate.<\/p>\n Louisville<\/strong> is as attractive to the eye as it is to the calculator. They\u2019ve been absolutely unstoppable so far this year. Whether or not they can maintain this pace (the probably can\u2019t) will be exciting to watch.<\/p>\n Alabama<\/strong> is going to crush Ole Miss<\/strong>.<\/p>\n Obviously, the predicted 20 point prediction for Ohio State<\/strong> over Oklahoma<\/strong> jumps out as improbable. But again, the Buckeyes have been on a tear to open the season and J.T. Barrett<\/a> is pretty experienced.<\/p>\n Penn State<\/strong> will win by more than 5 points on Saturday.<\/p>\n * – NGF is Nate\u2019s Gut Feel Theory<\/em><\/strong><\/p>\n Main Photo:<\/p>\nMETHODOLOGY<\/strong><\/h2>\n
P2PY Game Predictions — Week 3<\/strong><\/h2>\n
\nPrediction: Houston 26<\/strong> to Cincinnati 20
\nATS Winner: Cincinnati<\/p>\n
\n
\nPrediction: Florida St. 30 to Louisville 38<\/strong>
\nATS Winner: Louisville<\/p>\n
\n
\nPrediction:\u00a0Miami (FL) 29<\/strong> to App. St. 14
\nATS Winner: Miami (FL)<\/p>\n
\n
\nPrediction: Alabama 39<\/strong> to Ole Miss 21
\nATS Winner: Alabama<\/p>\n
\n
\nPrediction: Oregon 27 to Nebraska 37<\/strong>
\nATS Winner: Nebraska<\/p>\n
\n
\nPrediction: Texas A&M 28<\/strong> to Auburn 22
\nATS Winner: Texas A&M<\/p>\n
\n
\nPrediction: Georgia 26<\/strong> to Missouri 22
\nATS Winner: Missouri<\/p>\n
\n
\nPrediction: Ohio St. 42<\/strong> to Oklahoma 22
\nATS Winner: Ohio State<\/p>\n
\n
\nPrediction: Temple 20 to Penn State 25<\/strong>
\nATS Winner: Temple<\/p>\n<\/div>\n
\n
\nPrediction: Baylor 36<\/strong> to Rice 11
\nATS Winner: Rice<\/p>\nPrediction Notes Including NGFT* Analysis<\/strong><\/h2>\n