• Have reasonable expectations. Professional gamblers who make their living via sports betting win approximately 54- 58% of their wagers. That means that on average they lose more than 40% of their bets. Remember that these are averages. That means that in any given week a bettor may win 70% of their games and the following week lose 60%. The first week you may have made $700 on $1,000 worth of wagers but the next week, betting the same amount of cash, you lost $680. Over two weeks, you’ve turned a $20 profit. That’s to be expected in a real world scenario. (Of course, you still have your $1,000 bankroll.)
This may sound a bit simple, but what is really meant here is this – think like a fantasy owner. As a sports bettor, one has to respect the depth of statistical knowledge that fantasy players possess, and although it’s weird that they don’t generally care about the real NBA playoffs, they get a few things right. The ability of a successful fantasy basketball owner to identify the minutiae of statistical production across the span of four or five months is something every NBA bettor should attempt to emulate.
We will tell you this, though. The more intelligent and well-spent time you put into studying for your picks, the more successful you should be. Sports betting has a way of rewarding the people who are willing to put in the hard work and the long hours to crack the system and make better picks. There is no reason that this can't be you as long as you're dedicated.
The third model was based on a concept called expected goals. In this model, each shot a team makes is assigned a value based on historical data of shots taken in similar situations. For example, a shot from inside the box typically has a 12% probability of going in, so it contributes 0.12 to a team’s expected goals total. Shots from outside the box have only a 3% chance of going in and contribute 0.03. Summing up all expected goals scored and conceded by a team gives a good overall estimate of the quality of a team’s attack and defence that can then be used to simulate future matches. My model based on expected goals resulted in some spectacular gains early on in the season. It predicted the decline of Chelsea, but it overrated Arsenal and Liverpool. While the expected goals model didn’t lose money, it made such wild predictions that it couldn’t be relied on for a steady return. 
The second approach is to create a mathematical formula that gives you a percentage based on the stats and factors that you put into it. There is a multitude of different ways to build your formulas, but here is a general idea to get you started. Come up with the criteria that you think is important to figure out how likely a team is to win. This could be any number of criteria and usually the more, the better. <
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