Among the long list of new services and tools we will offer to our subscribers this season is betting advices. We will give our picks for every games of the National League, based on a proprietary model built and tested over multiple leagues.
Betting is a growing market all over the planet. In North America, it is even the next big source of money for the NHL who opened the rights to different bookmakers as local legislations are making it legal to bet on sporting events. This will come with a flow of new data made available thanks to chips put on pucks and players to make it possible to bet on things like how fast Connor McDavid will skate in a given game…
But let’s come back to Switzerland. We already presented how we will project games and standings thanks to our model in the article below.
This model has been used in France by Thibaud since 2018-19 and immediately grabbed the interest of the amateur sport bettors. Why? Simply because having a reliable Game probabilities model helps a lot to defeat bookmakers. We’ll get back to that.
Avant-propos
First thing first, this article is directed at people interested in betting money on hockey games. If you are not 100% comfortable with the idea of losing money (which is very possible), close that page and go do something smarter. Seriously, just go.
Betting should be a disinterested act but a thoroughly thought one. Once you have bet money, you should have no regret whatsoever. No “should have” or “could have”. The risk of losing must be accepted in order to avoid any frustration and a possible drift towards a dangerous addiction.
As an amateur sport bettor, find a bookmaker you like and make a deposit for a sum you have already accepted you could lose. That sum should do for a given period of time, using a very small percentage of your bankroll (like 3%) every time and not more. With no possibility to reinvest more money before the end of the given period of time.
The worst is, hockey is a very frustrating sport where you throw a tiny disk in the middle of a forest of legs, sticks, skates hoping it will go through. And the best team doesn’t always win. The other goalie could be a wall for one night, or the posts might work against you, etc. On a short term basis, hockey gods can simply hate your guts, or send you to heaven. But on the long term, there is a logical way to make it work.
How to bet on hockey?
The last few years, we have studied the market in order to build a model that would help us betting smart. This, for multiple reasons:
What team to bet on? We will only talk here of betting on the game winner. You can always bet on the number of goals or many other things but let’s stick to the basics. As we said, the favorite team doesn’t always win. Last year in France, the team with the best odds according to bookmakers only won in regulation time 55.7% of the time. We caught the last 83 games of NL and the best odds won just 49.4% of the time… Which leads to the next question:
Should you bet on the favorite team? If you look at the average odd for an easy pick, like Zug playing at home, you will end up with around a 1.7 odd for a win in regulation. That’s not much of a gain. You can win most of the time but only a couple of losses and you could end up with losing money. Or you can always bet on Langnau and hope for a miracle, but will the number of wins will be enough to end with a positive balance? So how do we do it?
What is a smart bet? If you wish to start betting with a method behind your picks, you need to choose your battles while asking the following question: is my bet worth being taken?
We need to take several steps to answer this question.
1/ Know your game probabilities: Anyone can guess the result of a game based on his/her knowledge of hockey but professional sport bettors use mathematical models to objectively do the probabilities for them. That where our own model comes in.
And the question is not here to pick Bienne over Ajoie, but to get an idea on closer match-ups, ones that bookmakers with, let’s say, less knowledge of the National League, will have a tougher time to assess. Like that Bern vs Fribourg. Bookmakers will look at the current standings and historical performances of a team to establish their odds. But they don’t know in details, like us, the detailed value of every player in the roster or what happens if the back-up starts. But mostly the standings don’t know if a team is overperforming and doomed to start losing, or the other way around.
2/ Identify your prey: The next step is to compare your game probabilities with the odds given by the bookmakers. Always following the favorite team is not always worth it. Sometimes the team with the lesser probability has such an high odd that they become more interesting. Here, on March 9th, Biel, with the lower probability at 47% but a 3.1 odd was the interesting pick to make. One that paid off as well.
And there are concrete examples of games where bookmakers are simply in the wrong. Like this one, on March 12th, where Fribourg had the best odds, thanks to their current standings, but our model actually knew that Geneva was a better team. A win-win situation for us.
Results for 2020-21
Last year we tested the model in France, NHL and the last part of the NL season. Over 83 games, only 33 were deemed worth a bet. And though we won just 48% of them, the return on investment was of 53%.
Basically, Biel-Bienne and Rapperswil were our darlings, while we didn’t even bet once on Zug. Small sample you can say, and yes. But over a full season in France, where bookmakers know nothing of the league, we ended with a 95% ROI… No promises are being made here, and should never be done with sports betting, but we are confident that the model should work.
So this season we will offer our daily picks to subscribers, according to the model. You will be free to trust the process, half trust it and half go with your guts, or bet against the model… As long as you have fun along the way.
DISCLAIMER: We’re not linked or sponsored by any betting platform and we have no interest in recommending any particular platform. Here, we also want to showcase what can be done with the use of statistics in sports.
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You can also find some more statistics on NL Ice Data here: nlicedata.com
this seems interesting. One thing bookmaker seems to miss is the absence of important players. Does your model takes into account if top players are missing due to injury/disqualificaiton etc? and how that would impact line chemistry etc? that would prompt me to subscribe.