Originally posted Tuesday, November 3, 2015 at probabilis.blogspot.com
In recent years, the term "Clemsoning" has become synonymous with a team shockingly losing a game in which they were large favorites. While the origins of attributing the phrase to Clemson aren't concrete, Clemson has experienced more than its fair share of mind boggling losses, and it may have started with their 2 TD loss to Georgia Tech in 2011.
Related: West Virginia just scored again!
But this is the ACC! There's wealth to be spread! This is the conference that gave us this:
And this:
And this:
That last game (NC State over Florida St.) is an example of Clemsoning, and is one of the inspirations for this post: NC State was a 7/1 underdog in that game. With the ACC's consistently maddening mediocrity and tendencies for upsets, could you profit off of ACC teams "Clemsoning" in conference play?
Thanks to Prediction Machine's Trend Machine, I was able to easily pull all ACC conference games since 2011 (the year "Clemsoning" appears to have started) and look at how often the underdog won, and what the payoff would've been had you bet on that team. If you had simply bet underdogs against the spread, you would've won 52% of the time, which would've been a losing strategy (you need to win 52.38% of spread bets to break even). But we don't care about that! We want straight up victories, the kind that lead to celebrations like this!
The underdog won the game outright 29.13% of the time, which is quite a bit more than the average of around 20.43% (see: "Line (updated)"). Had you blindly bet the underdog in each game, you would've returned a profit of +910 units, which equates to a 3.96% ROI over the past 4 years. So not that much. However, the emotional return is priceless:
Originally posted Wednesday, May 27, 2015 at probabilis.blogspot.com
Here are the MDS Model's win total over/under picks for the 2015-2016 NFL season. The calculations are pretty simple: I used the Composite component my model (which is a composite (thus the name) of the Matrix component (only takes into accounts wins and losses) and the Pyth component (strength-of-opponent adjusted Pythagorean expectation)) to determine a win probability for each matchup, and then summed each team's schedule to predict their number of wins. The standard deviation in a team's wins is 2, which was determined both mathematically and via a short simulation (which then allows me to estimate the probability each pick (over or under) is correct).
Win totals were gathered from this article, and are updated as of May 8.
| Division | Team | Projected 1st | Team | Projected 2nd | Team | Projected 3rd | Team | Projected 4th |
| NFC East | DAL | Predicted | 10.26 | PHI | Predicted | 9.56 | NYG | Predicted | 7.17 | WSH | Predicted | 5.31 |
| | O/U | 9.5 | | O/U | 9.5 | | O/U | 8 | | O/U | 6 |
| | Pick | Over | | Pick | Over | | Pick | Under | | Pick | Under |
| | Prob | 64.76% | | Prob | 51.24% | | Prob | 66.16% | | Prob | 63.43% |
| NFC West | SEA | Predicted | 11.69 | ARI | Predicted | 8.71 | SF | Predicted | 7.33 | STL | Predicted | 6.79 |
| | O/U | 11 | | O/U | 8.5 | | O/U | 7.5 | | O/U | 8 |
| | Pick | Over | | Pick | Over | | Pick | Under | | Pick | Under |
| | Prob | 63.56% | | Prob | 54.23% | | Prob | 53.42% | | Prob | 72.68% |
| NFC North | GB | Predicted | 10.39 | DET | Predicted | 8.50 | MIN | Predicted | 6.37 | CHI | Predicted | 5.62 |
| | O/U | 11 | | O/U | 8.5 | | O/U | 7 | | O/U | 7 |
| | Pick | Under | | Pick | Over | | Pick | Under | | Pick | Under |
| | Prob | 61.92% | | Prob | 50.09% | | Prob | 62.38% | | Prob | 75.55% |
| NFC South | NO | Predicted | 8.49 | CAR | Predicted | 7.86 | ATL | Predicted | 7.85 | TB | Predicted | 4.81 |
| | O/U | 9 | | O/U | 8.5 | | O/U | 8 | | O/U | 6 |
| | Pick | Under | | Pick | Under | | Pick | Under | | Pick | Under |
| | Prob | 59.99% | | Prob | 62.61% | | Prob | 53.06% | | Prob | 72.33% |
| AFC East | NE | Predicted | 11.75 | BUF | Predicted | 9.31 | MIA | Predicted | 8.52 | NYJ | Predicted | 5.84 |
| | O/U | 10.5 | | O/U | 8.5 | | O/U | 9 | | O/U | 7 |
| | Pick | Over | | Pick | Over | | Pick | Under | | Pick | Under |
| | Prob | 73.47% | | Prob | 65.75% | | Prob | 59.44% | | Prob | 71.91% |
| AFC West | DEN | Predicted | 10.91 | KC | Predicted | 9.54 | SD | Predicted | 8.32 | OAK | Predicted | 4.24 |
| | O/U | 10 | | O/U | 8.5 | | O/U | 8 | | O/U | 5.5 |
| | Pick | Over | | Pick | Over | | Pick | Over | | Pick | Under |
| | Prob | 67.49% | | Prob | 69.82% | | Prob | 56.29% | | Prob | 73.52% |
| AFC North | BAL | Predicted | 9.29 | PIT | Predicted | 8.64 | CIN | Predicted | 8.28 | CLE | Predicted | 6.25 |
| | O/U | 9 | | O/U | 8.5 | | O/U | 8.5 | | O/U | 6.5 |
| | Pick | Over | | Pick | Over | | Pick | Under | | Pick | Under |
| | Prob | 55.79% | | Prob | 52.88% | | Prob | 54.43% | | Prob | 54.89% |
| AFC South | IND | Predicted | 10.21 | HOU | Predicted | 9.26 | JAC | Predicted | 4.56 | TEN | Predicted | 4.35 |
| | O/U | 10.5 | | O/U | 8.5 | | O/U | 5.5 | | O/U | 5.5 |
| | Pick | Under | | Pick | Over | | Pick | Under | | Pick | Under |
| | Prob | 55.73% | | Prob | 64.76% | | Prob | 68.06% | | Prob | 71.76% |
For what it's worth, I went 16-15-1 two years ago, when I only used each team's straight Pythagorean expectations. The MDS Model takes into account a lot more factors than that of two years ago.
