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.
