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PuckLuck Primer: 10/17/23

In what was our biggest night yet, we banked over 16 units by hitting seven of our eight suggested bets. It's just another night to an explosively profitable start to the season in a sport the general public considers one of the toughest to bet. In yesterday's Primer, in fact, subscribers were able to view the four bets we named that all hit. You're welcome.


Why bet hockey? Well, simply put, because there's not enough attention paid to it. I truly believe our model and analysis is lightyears ahead of sportsbooks and the betting public, leaving an edge that just normally isn't there in sports betting.


Since it's a new season and there's a lot of new faces, let me give a quick synopsis of how the model works. I created a player-based model to predict team outcomes, meaning each player is assigned a predictive value of goals-for and goals-against when on the ice through statistical regression and other predictive methods.


These values are broken down to each phase of the game - even-strength, powerplay, and shorthanded - since the state of the game drastically changes based on which situation a player's team is in.


We can also assume just how many of these goals a goalie is projected to save over expected, thanks to our predictive GSAx (goals-saved above expected) based on a goaltender's recent history.


Now, every model has strengths and flaws. In the past, the PuckLuck model has a reputation for being goaltender-heavy. To me, this was generally a safe "flaw" to have, since the goalie is the only player to play all 60 minutes in a game (most of the time).


Measures have been taken to constantly test and improve the model though, so I believe the extreme goalie bias is a thing of the past. So far, I'm really liking the predictive results we're displaying, and obviously it's paying big dividends to begin the season.


Also, because the model is in fact player-based, it fits hand-in-hand with the player projections for player props and daily fantasy lineup building. It may seem obvious to set it up that way, but most NHL betting sites and touts do not do this due to the extensive and complex nature of the statistical engineering involved. Yes, they're cutting corners elsewhere.


Thanks to years of refining, we're now able to tell you just how much a Matt Boldy injury will affect the Minnesota Wild in both the short and long term, for example. Our true player evaluation can easily adjust to the day's lineup shuffle, backup goaltender getting the start, or even how a new call-up projects to perform.


And with that said, let's get into how to profit from today's glorious nine-game slate:

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