Picking 2013-2014 NFL win totals

My methodology uses each team's strength of schedule and win probabilities for each game to determine their expected number of wins in the upcoming season. In making each pick, I consider both value on the betting line (acquired from Bovada) and also making the strict over/under pick (assuming even money on either side). The following picks for each team are ranked from most likely to least likely; note that a moneyline pick is only included if it has value.

Team: Kansas City Chiefs

O/U: 7.5

Pick: Under (90.83%)

Moneyline: U @ -125

Team: Philadelphia  Eagles

O/U: 7.5

Pick: Under (84.95%)

Moneyline: U @ -125

Caveats on sports picks

A few additional points on my picks:

• I will never pick for or against Carolina. In any sport. You just don't do that.

• Inversely, I'll never pick for or against Duke. I cheer for two teams: Carolina and whoever's playing d00k.

• I'll never post a pick for any of my other favorite teams either, which really only include the Tampa Bay Rays.

• The picks are rated 1-5, but 4- and 5-star picks may not necessarily be "locks". Instead, it indicates a higher expected payoff versus the moneyline. While this often does imply a higher probability of winning, it may not pick the huge favorite every single time. 

Instead of thinking in terms of "for sure wins", look at things in terms of probabilities. Even if a favorite has a 90% chance of winning, that still means 10% of the time they're going to lose. The goal is to find when everyone else thinks that underdog won't ever win: knowing that in fact sometimes they will. We're concerned with outcomes in the long run and consistency. 

Betting systems and strategies

For the past couple of months, I've been refining a system of mathematical models that estimates win probabilities for outcomes of sporting events in various leagues. I then use these results to determine value on moneylines and spreads. The betting strategy is ultimately built upon the predictive capabilities of crowd sourcing, aggregating data, and finding value.

I've developed strategies for NBA, NFL, MLB, NHL, NCAAF, NCAAB, WNBA, and CFL, and consider the following models/rankings in my system:

• TeamRankings (NBA, NFL, MLB, NCAAF, NCAAB)

• NumberFire (NBA, NFL, MLB, NCAAF, NCAAB)

• Jeff Sagarin's USA Today ratings (NBA, NFL, NHL, NCAAF, NCAAB)

• Log5 (based on teams' winning percentages) (NBA, MLB, NHL, WNBA)

• Pythagorean Expectation (originated by Bill James) (NBA, NFL, MLB, NHL, WNBA, CFL)

• KenPom (NCAAB only)

• Seven Overtimes (NCAAB only)

• ESPN Consensus data (NBA, NFL, MLB, NCAAF, NCAAB)

• Covers Consensus data (NBA, NFL, MLB, NHL, NCAAF, NCAAB, WNBA, CFL)

I then use the following criteria to determine my picks:

• For individual games and props, I only take value >= 2.5%

• For series futures, I only take value >= 5%

• For season futures, I only take value >= 10%

Finally, I grade these picks on a 1-5 star scale based on multiple criteria, including public consensus, whether the models strongly agree with one another, etc. Starting August 3, I'll begin posting my daily picks on the blog, as well as tracking them on my Covers account.