I've been using this for post-season for a few years now. You can evaluate how effective or accurate it is by looking at previous predictions, all of which I've been willing to make public, including the one at this link:
https://www.tidefans.com/forums/showthread.php?t=279457&p=2966032&viewfull=1#post2966032
I make no claims to have any supernatural knowledge, don't bet on this basis. But looking at the numbers and figuring, it has been very good at determining the final margin or close to it even if not all the details.
PAST USES OF THIS MODEL
2013 BCS Title Game: Alabama 28 Notre Dame 7
2014 Sugar Bowl: Alabama Ohio State pick 'em (34-34)
2015 Cotton Bowl: Alabama 31 Michigan State 10 (I fudged it to 17 because I couldn't believe it)
2016 Title Game: Alabama 27 Clemson 17 (got the score wrong but we were up by 12 with seconds left)
Super Bowl XLIX: Seattle 28 New England 24 (hey, if Pete Carroll hadn't phoned Les Miles......)
Super Bowl XL: Carolina 28 Denver 23
2016 Peach Bowl: Alabama 30 Washington 16
2017 CFPNCG: Alabama 31 Clemson 17
Super Bowl XLI: New England 31 Atlanta 27
The model so far is basically 6-3. One loss can be chalked up to Pete Carroll's stupidity and another to the unfortunate combination of Bo's injury and two pick plays - not to deny Clemson their deserved due.
Btw - some predictions even in the above post were accurate.
Alabama DID get 31 points.
Clemson DID turn the ball over twice.
My prediction was ALSO almost incumbent upon us getting a NOT - which we damn near did if you recall.
And the biggest failure? Bo getting hurt. Seriously - if he'd lasted one more drive, we win.
So let me explain what I do.
1) Eliminate the cupcake games that inflate stats.
2) Deduct the scores from within the game in question to determine the other stats for scoring offense/defense (e.g. when evaluating LSU's corrected scoring offense, I deduct their cupcake games PLUS the Alabama or Georgia game - that's why the totals are different).
3) Get a total average performance based on all the data points (8 for Alabama, 9 for UGA)
4) Figure how much weight to give to common opponents
5) I did NOT eliminate the stats regarding rushing and passing yards. Will it substantially affect them? Maybe, but it's getting too close to the game, and I've never done it before.
Next post will contain the data followed by a post with a prediction.
https://www.tidefans.com/forums/showthread.php?t=279457&p=2966032&viewfull=1#post2966032
I make no claims to have any supernatural knowledge, don't bet on this basis. But looking at the numbers and figuring, it has been very good at determining the final margin or close to it even if not all the details.
PAST USES OF THIS MODEL
2013 BCS Title Game: Alabama 28 Notre Dame 7
2014 Sugar Bowl: Alabama Ohio State pick 'em (34-34)
2015 Cotton Bowl: Alabama 31 Michigan State 10 (I fudged it to 17 because I couldn't believe it)
2016 Title Game: Alabama 27 Clemson 17 (got the score wrong but we were up by 12 with seconds left)
Super Bowl XLIX: Seattle 28 New England 24 (hey, if Pete Carroll hadn't phoned Les Miles......)
Super Bowl XL: Carolina 28 Denver 23
2016 Peach Bowl: Alabama 30 Washington 16
2017 CFPNCG: Alabama 31 Clemson 17
Super Bowl XLI: New England 31 Atlanta 27
The model so far is basically 6-3. One loss can be chalked up to Pete Carroll's stupidity and another to the unfortunate combination of Bo's injury and two pick plays - not to deny Clemson their deserved due.
Btw - some predictions even in the above post were accurate.
Alabama DID get 31 points.
Clemson DID turn the ball over twice.
My prediction was ALSO almost incumbent upon us getting a NOT - which we damn near did if you recall.
And the biggest failure? Bo getting hurt. Seriously - if he'd lasted one more drive, we win.
So let me explain what I do.
1) Eliminate the cupcake games that inflate stats.
2) Deduct the scores from within the game in question to determine the other stats for scoring offense/defense (e.g. when evaluating LSU's corrected scoring offense, I deduct their cupcake games PLUS the Alabama or Georgia game - that's why the totals are different).
3) Get a total average performance based on all the data points (8 for Alabama, 9 for UGA)
4) Figure how much weight to give to common opponents
5) I did NOT eliminate the stats regarding rushing and passing yards. Will it substantially affect them? Maybe, but it's getting too close to the game, and I've never done it before.
Next post will contain the data followed by a post with a prediction.