Last we convened, we were wrapping up the unofficial first half of the NHL season, managing a 10-10 week through six days of daily picks that netted +1 unit. Neither element of that short-term record is all that impressive, but if we managed to finish every week in the black, we'd gladly take it.

The randomness of betting hockey - particularly in the regular season when the game fundamentally changes if it's tied through 60 minutes - makes it hard to pick games at better than a 50-50 rate. So why make it difficult for yourself by betting on teams that average -150 or higher? Why set the bar of success at 60% when you don't have to?

Of course, setting the bar for profitability at or below .500 means betting plus-money underdogs - the worst team in the matchup. And sure, those teams win all the time. The problem is trying to make a case, in print or aloud, for the underdog in matchups like Ducks-Avalanche, Blue Jackets-Oilers, Senators-Maple Leafs, and Blackhawks-Flames: all games the underdog won in the week leading up to the All-Star break.

We know the favorite isn't 100% guaranteed to win any NHL game, but how can you make an argument for why tonight is the night the road underdog shocks its high-caliber opponent?

That's where comparative pricing comes in. The only real argument for backing the Ducks to fly into Denver to beat Colorado is the fact our numbers suggest that Anaheim wins 29 times out of 100, but the moneyline suggests the Ducks pull off the upset 24 times out of 100.

That 5% disparity might not pay off in one game, but we're not actually betting one game: We're betting hundreds of games over the course of a season and over the course of our betting life. Sometimes those ugly, uncomfortable bets are on teams from Anaheim. Sometimes they're from Columbus, Ottawa, and Chicago. In all of those bets, we expect those teams probably lose that night, but over a large enough sample size - our lifetime - they win slightly more than the market suggests, and a sub-.500 record on the ice still provides a positive margin in the betting ledger.

With the stretch run upon us, we'll match the intensity of the playoff push with biweekly articles - Monday weekday and Friday weekend editions - of our price comparison tool in an effort to be as accurate as possible.

The recipe

We started the campaign using regular-season point totals as a baseline for rating teams since it's our best measurement. Throughout the campaign, we adjust club ratings using on-ice metrics to remove the cognitive bias of win-loss records, which can be skewed by outliers like special-teams results, poor goaltending performances, and other unreliable events.

The cheat sheet

There are no bad bets at the right price, but how do we know what a good price is?

The following includes my fair price on the games (true moneyline) and the moneyline price I'd need to bet either side. I only need a 1% edge for a favorite if we're getting better than a fair price on the team more likely to win. For the underdog, I'll need 4% or better to make it a bet. For games I project to be closer to a coin flip, a 2.5% edge is enough for a worthwhile wager. I also have a 5% win probability consideration for a team playing in the second game of a back-to-back with travel and a 3% consideration for a team on the second leg of a back-to-back without travel. When it comes to injured players, I do my best to estimate the impact on their team's win probability.

When the betting markets open up the night before, you can compare those prices with our "price to bet" column to see if you're getting any value with either side's moneyline. There's also a possibility that a moneyline moves into a bet-friendly range at some point between market open and puck drop.

Matt Russell is a betting writer for theScore. If there's a bad beat to be had, Matt will find it. Find him on Twitter @mrussauthentic.

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