Computers have been involved in sports betting for decades, well before the internet era. The ability to predict the future of sports betting through math algorithms is considered one of the holy grails of gambling. Despite the rapid advancement of powerful computers capable of processing billions of calculations per second, surprises and upsets still occur in all types of sports leagues. Canada Sports Betting experts try to help our readers by making available several tips in our Free Picks page.
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Computer Picks & Score Predictions
Computer picks benefit from the rigors of dispassionate math, but human uncertainty still creates surprising results on a regular basis.
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Football’s the most popular sport to bet on in the United States, with billions in wagers committed every season. Computer picks tend to be individual matches and point spreads.
Algorithms also simulate over/unders and many types of props well while futures and other types of bets which involve longer periods of time tend to be less reliable. Predictions become less tenable because of the many issues which may interfere with a successful outcome. An injury to an important player may ruin an entire season, preventing a successful wager.
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The Canadian Football League is the oldest pro association in North America, with the most rabid fans hailing from Saskatchewan. Despite organizational issues, the CFL still attracts some of the best pigskin talent from the United States.
Since there’s a fewer number of franchises competing in the CFL compared to its bigger brother, computer picks for Canadian football contain a smaller sample size. This leaves a bit more room for upsets compared to American football.
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Considered one of the most predictable leagues in professional sports, luck factors into betting on the National Basketball Association less than other leagues.
Basketball features a smaller roster than other team sports, increasing the influence of elite players like Steph Curry, James Harden and LeBron James.
Typically, bettors focus on spreads because straight up moneylines tend to be more lopsided, reducing the profit for wagering on the favorite.
One of the most prevalent regular season trends consists of top teams underperforming during the regular season, staying fresh for the playoffs. This wreaks havoc on computer predictions for basketball, especially for futures involving win totals and conference winners.
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Of all North American leagues, the NHL features the highest level of parity among franchises, increasing the uncertainty of making predictions. A tight salary cap, the importance of goaltenders and the unpredictable ways a puck bounces help contribute to stunning upsets, such as the Vegas Golden Knights amazing run to the Stanley Cup finals.
Goal differential tends to provide a superb measure of how well a franchise plays, especially when attempting to measure playoff outcomes. Computer projections for hockey work well for individual player production, as long as the player doesn’t experience a season-altering injury.
The axiom “defense wins championships” applies to hockey, which continues to evolve towards a more cautious approach.
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The NBA changed when teams fully realized that three points are more than two points, dragging the offense to the perimeter. Baseball’s been forever altered by analytics too, emphasizing the power game more than any other time in the history of the sport. Strikeouts have become far more acceptable, as long as the hitter striking out socks 30 dingers a year.
Pitching still appears to be the limiting reagent for success in professional baseball, particularly when attempting to predict the playoffs, when rotations shorten.
Despite the fact that this sport’s relatively unpredictable compared to basketball and football, computer picks still perform well for straight up wagers and run totals.
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Major League Soccer’s still expanding after celebrating its 20th anniversary in 2016. The talent level of this league has increased dramatically since the designated player rule allowed teams to throw big money at international stars, leading to a more competitive environment. Toronto FC, the best team in MLS history, could miss the post season a year after their historic run.
Advanced analytics tend to split the field in three – key passes and scoring chances measure the effectiveness of offensive players, ball recovery and interceptions reveal the quality of midfielders while pitch positioning and pass totals imply strong possession. Popular computer picks include individual matches, totals and futures.
Computers Simulate Probabilities – Not Guarantees
There’s no such thing as certainty when predicting sports events.
Probabilities may show that one team has a massive advantage over another, but there’s never a guarantee, no matter how lopsided the matchup appears.
Computers aren’t yet capable of predicting the unexpected. Players having an off day, lucky bounces and bad beats happen on a regular basis, injecting uncertainty into all sporting events. Sometimes, players transcend limitation unexpectedly, causing massive upsets and historic results.
While not frequent, injuries do happen in-game, another issue which simply cannot be predicted via computer model. Despite the increased reliance on algorithms to determine risk and reward in sports betting, there simply isn’t sufficient data available to literally predict the future.
Sports Computers Require Human Guidance
Self-learning algorithms and artificial intelligence have made great strides over the past decade or so, but humans still direct the activities of digital processes.
Computers simply crunch numbers. The meaning of these numbers requires human context to make sense, especially in the realm of sports betting.
Prediction models receive constant adjustments to improve the quality of the sports picks made by computers. For example, previous algorithms for NHL games may have relied on goal scoring numbers in the past, while current prediction models may focus more on the ability for a team to prevent goals.
Various computer prediction software attempt to outperform each other every year, slowly improving the accuracy of computerized sports bets over longer periods of time.
The Westgate SuperContest is one example of a competition which pits different computer models against each other for large sums of money.
Computer Picks FAQ
Human emotion and cognitive bias are the main enemies of successful sports betting. Computers eliminate the human factor from predicting outcomes, increasing the efficiency and accuracy. Cognitive bias revolves around opinions that appear to be logical at first glance, but have no basis in math.
The gambler’s fallacy is one of the more popular type of cognitive bias. Put simply, an event which occurred frequently in the past isn’t less likely to happen in the future.
For example, over a long period of time, coin flips trend close to 50/50, but that doesn’t mean that the next coin flip is more likely to be tails if heads was the winner five times in a row. Eliminating this type of flawed decision-making improves sports wagering results, especially over the long term.
Paying for picks is a personal decision which depends on your gambling goals and the amount of time and effort available to make your own picks.
Paying for picks may be considered similar to hiring an expert for financial investments. There’s no guarantee that your investment will create profit, but there’s a good chance that computer-guided expert picks will help you grow your bankroll, compared to your usual wagering patterns.
Online betting refers to the use of a computer or mobile device to places bets through an Any sport which generates numerical stats will be a candidate for computerized picks, including hockey, football, baseball, basketball, soccer, horse racing and boxing.
The greater the dataset available, the higher the probability that computer picks will reflect an accurate prediction. Mountains of data are available for all major North American sports leagues, often dating back decades.
As such, computer models for popular sports tend to offer a solid level of accuracy.