A holiday Monday means matinee action in the NHL. To celebrate the last holiday afternoon games of the regular season, we'll play our own fun game, using what every sports bettor wishes they had - a time machine.

Unfortunately, this time machine has a catch: We'll get to know everything about the games - except the actual goals.

Let's apply this magical circumstance to real games from last week. We get to know which team created more high-danger scoring chances at even strength and the percentage of expected goals their five-on-five attack generated - two pretty important indicators for success.

Game 1

Game 2

As a bonus, we also get to know that Team C was given seven power plays but didn't score on any of them. Which team would you want to bet on before the game? The -200 favorite that went scoreless on the power play but had a minor edge at even strength, or the +170 underdog?

For long-term profitable betting, both answers should be Team B - the San Jose Sharks. Yet in both cases, they lost - 3-1 (empty-net goal) to the Pittsburgh Penguins and 2-1 to the Vegas Golden Knights.

San Jose got surprisingly good goaltending from Aaron Dell (.926 save percentage) and Kaapo Kahkonen (.947 SV%), didn't allow a goal on special teams (10 out of 10 penalty kills), and was cumulatively level with its opponent at even strength. However, even with all this time-travel-assisted information, we would've made good bets that lost.

Here's how season-long metrics look for each team.

Even without a time machine, you can see how we might expect the Sharks to outplay the Penguins at home and compete stride for stride with the Golden Knights - even if the puck didn't bounce their way around the net.

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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