Sports betting is one of the most popular ways to combine our favorite sports with the chance to make some money. Everyone placing a bet hopes that their prediction will be correct, but there’s no sure way to guarantee that you’re in the money. Advances in math and science have opened up new statistical methods of sharpening prediction accuracy, which algorithms allow us to do.

Betting algorithms are one of the best tools in a bettor’s arsenal. These are computer applications designed to utilize large data sets to predict the outcomes of matches or other variables in a sport that bettors might be wagering.

In this piece, we’ll be taking a look at the world of sports betting algorithms and sports betting models, exploring what exactly they are, how they work, how effective they are, which sports they are useful for, and more. If you hope to learn how to win at betting, this is a great place to start.

Let’s get right into it.

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What is a Sports Betting Algorithm?

As defined by mathematicians and computer scientists, an algorithm is defined as a sequence of finite, well-defined instructions used to perform computations or solve specific classes of problems or answer complex questions. What a betting algorithm will do for you is identify what will be a profitable bet for you to get into.

Algorithms for sports betting have only recently become prominent tools in the world of betting, as people saw their potential predictive value. The rise of computational power first fueled the use of algorithmic predictions in the world of finance, where traders needed to make complex decisions factoring in time, volume, and price with precision. Bettors saw the potential here and developed algorithms that would help them make more accurate predictions.

How do Betting Algorithms Work?

An effective algorithm will function by taking in data such as a team’s match history, player statistics, home-field advantage, injury rates, and so on, then analyzing it according to the rules defined by its instructions. A good algorithm will not only suggest potential winning bets for you but may even suggest how much you should bet according to its level of surety.

As with all computer systems or programs, an algorithm will only be as good as its underlying programming. While human beings are still more effective in interpreting new data and nuanced information, the combination of human intelligence and today’s computational power is powerful. Many draw a correlation between algorithms and Artificial Intelligence, but these are two different phenomena even though they share some common elements.

What are the Different Types of Sports Betting Algorithms?

There are two basic approaches taken by the designers of sports betting algorithms. You have the option of choosing between value betting algorithms and arbitrage betting algorithms. The separation is determined chiefly by what a bettor hopes to achieve with their bets.

Value Betting Algorithms

For several reasons, value bet algorithms are the most widely available and popular types of algorithms used by sports bettors. Value is an important term to understand here, so let’s get into it a bit.

Say you have a game between teams A and B. Should both of these teams have the same stats on the books, either team will have a 50% chance of winning. In the betting world, this will translate to odds of 2.00. This is what we refer to as probability or chance.

Imagine we have two bookmakers offering odds of 1.90 and 2.10 for team A to win. Which will be the better option for bettors? Here’s how we calculate it and find which has value:

Probability x Odds – 100% = Value

So, in this case, the formulation will be as such:

• 1st bookie: 50% x 1.90 – 100% = -5%
• 2nd Bookie: 50% x 2.10 – 100% = 5%

Faced with these options, the second bookmaker will be a clear choice, as they offer positive value and greater chances of making money on your bet. This is a value bet.

Now, bookies are not in this business to lose money, so such a scenario is unlikely to happen. What betting algorithms do for us is give us a sharper edge on the predictions made by the bookmakers. The value of your bet will depend on the disparity between your calculated odds and what the bookies are offering.

While a good algorithm and betting model will bring you returns, you shouldn’t think of it as the end of your troubles. A sound system will only be half the story. For success, one will also have to decide how much money they place on the bets their algorithms present, otherwise known as bankroll management.

The warning not to put all of one’s eggs into one basket applies here, as you don’t want to lose all your money on one failed bet. Remember, there’s no sure bet out there unless you’re doing something shady, which means that there’ll always be a chance of failure no matter how good the algorithm you’re using is. According to the confidence or surety your algorithm indicates, bankroll management also entails determining how much money to place on a particular bet.

Arbitrage Betting Algorithms

Arbitrage is a term common in finance that describes the practice of making a profit by taking advantage of price differentials in stocks, currencies, or other financial assets. In the world of sports betting, an arbitrage involves taking advantage of changing odds assigned to the outcome of sports events.

Arbitrage is typically confined to betting exchanges, whereby bettors can make their initial bets at odds in their favor and then go ahead to make another bet that goes against their initial bet. The outcome is that they will be guaranteed a profit regardless of the result should the odds shift. With arbitrage, your sports betting algorithms will not be trying to predict any outcomes of sporting events but will instead be searching for suitable patterns in the odds attached to an event.

What Types of Data do Betting Algorithms Need?

GIGO (Garbage In Garbage Out) is a term used in the computing world that aptly describes how systems process data. Good data will give you useful information, while bad or insufficient data will give you useless output. Any algorithm will be designed with a sport in mind. The data points used in sports betting tend to be relatively straightforward and clearly defined.

A predictive algorithm for use in basketball betting, for example, will take in data points such as home winning rates, points per game, individual player statistics, rebounds, and so on. All the data that a sports betting algorithm might need is freely available in today’s digital age. Even so, not all data is created equal.

An algorithm taking in thousands of useless, irrelevant facts will fail to predict outcomes with the accuracy of sports betting algorithms with a handful of solid, relevant data points. Quality over quantity applies to the betting world when it comes to data in a big way.

Who Creates Sports Betting Algorithms?

Sports betting and finance have a lot of overlays that manifest themselves in various ways, with the use of algorithms being just one example. Bettors quickly followed suit when bankers and stockbrokers harnessed the power of computers to accomplish complex trades and make predictions on how the markets would behave.

The same minds behind creating the algorithms used in finance are the ones creating sports betting algorithms. The same principles of computer science and mathematics dealing with statistics and hard data points on wall street are easily translated to the world of betting.

One key element that made this shift so desirable and effective is that human error (typically caused by emotional bias) is eliminated from these transactions. A human might be inclined to bet on their favorite baseball team regardless of their game history. A stockbroker might buy into a losing stock because they already had money invested in it, what’s known as the sunk-cost fallacy. Algorithms do not have such biases affecting their operation and output.

There are no sure investments, just as there are no sure bets. All we can do is try and get the best odds possible, and this is what mathematicians and computer scientists try to do when creating betting algorithms.

The prospect of creating sports betting algorithms will be a daunting one, especially if you don’t have any experience with advanced computational statistics or data science. Various factors need to be considered, and your knowledge of the game, however expensive it might be, will not compensate for your lack of expertise in these fields.

This is why most sports bettors choose to use ready-made algorithms, whether they are paid for or free applications. There are countless sports betting algorithms out there, so many that picking one might pose a challenge. You will, unfortunately, encounter plenty of scams and subpar programs out there that you should steer clear of.

Note that the best and most effective algorithms out there are not free of charge – why would the creator of such an algorithm give it away for free to help other people make money rather than keep it to themselves?

An excellent way to go about the selection process is to check out reviews and discussions on whatever boards, forums, and other online resources you get the chance to look into. As we said, however, people who have successful algorithms tend not to go around advertising the fact, so be careful when considering any recommendations.

The best services will typically have a reputation for extensive sports knowledge, long-term betting success, user-friendliness, and accessible algorithms. Should you be a newcomer to the world of algorithmic and modeled sports betting, seek out services that operate on spreadsheet formats such as Microsoft Excel, Google spreadsheets, and so on. Especially spreadsheets are the best first sports betting algorithms software for new bettors.

What are the Downsides of Betting Algorithms?

There’s no such thing as a perfect sports betting algorithms. No program can be designed to make flawless future predictions, no matter how much past data it is fed with. Betting algorithms are handy tools for bettors, but they still have some drawbacks that make them imperfect.

For one, they are entirely dependent on the quality of the data inputs they receive. Bad or inaccurate data will result in erroneous results, and the algorithm will have no way of differentiating one from the other.

Secondly, sports betting algorithms rely on us to provide useful data points for their analyses. This means that any tips, insights, or starting lineups for upcoming games will be made available to the public at certain specified times, meaning everyone, bookies included, will have access to new information at the same time.

Perhaps the most significant challenge that sports betting algorithms face is that they cannot create full pictures of the sporting events they are analyzing. They can only make particular snapshots based on the data they receive. Algorithms have no way to gauge shifts in the momentum of a game, team psychology, or the emotional state of individual players.

What are Computer Picks?

Computer picks are predictions made by computer programs based on a team’s history and performance trends to make projections about their performance. These programs are run on sports betting algorithms, as we’ve covered above. Computer picks are usually presented in a table format, with random upsets excluded since computer projections don’t account for them.

A typical computer pick table will have projections based on 100 or so previous games, detailing the spreads, totals, winners, and other stats. They offer a chance for bettors to make their own decisions based on the data points they consider to be most pertinent, which will often be the difference between

Statistical analyses have become the mainstay of betting projectionists, with leagues such as the NBA being the most heavily analyzed. A computer pick table for the NBA might be created by running over 10,000 simulations on a powerful computer to arrive at its predictions.

Many bettors, however, prefer computer picks over expert predictions because such picks do not suffer from the vulnerabilities and biases that human beings are prone to. Even so, computers picks are not perfect predictors of future outcomes. They can only make theoretical predictions, meaning that any bettor will need to consider other factors if they hope to have a true edge on the open betting market.

What are Sports Betting Models?

Sports betting models are, perhaps, the best way for bettors to use the predictive power of computer algorithms and beat the bookmakers at their own game. A betting model will take all the estimated probabilities relating to a sporting event and synthesize a more accurate prediction than what the bookmakers have. When this prediction is correct, bettors will make money on the bets they had placed, but this might not always be the result.

Some people have trouble believing that sports betting models work, but this can easily be explained in a way everyone understands. These models work by taking various data points and historical information into account when making their predictions. The idea is not necessarily to predict the future but to be more accurate than the bookmakers setting the odds for a given sport or event.

How to create sports betting algorithm?

Setting up a good predictive algorithm for sports betting is a highly involving task – one which very few people have the time, research skills, knowledge, and motivation to attempt. This is why you will not find any good models on offer for free. Should you wish to give it a shot, you’ll need to follow the steps outlined below:

• Pick your preferred sport or league: The NBA, NFL, MLB, Tennis, FIFA, and so on all make for potential subjects for your model. All the information you might need is freely available online going back many years.
• Determine your problem: Put down what you want your model to predict. If you intend to be making value bets, then it should be designed to output predictions on events where you have better projections than the odds that bookmakers have come up with.
• Pick your tools: You will need to create your algorithm and program it using your preferred programming language, although the most accessible and user-friendly options are Google spreadsheets and Microsoft Excel.
• Do your research: You will need to dig up as much data as you can about the teams or leagues you are interested in so that your model has the biggest and deepest data set to work with, which will determine its accuracy and usefulness.
• Choose your methods: Depending on the particular outputs you desire or problems you want to solve, you’ll need to figure out what the most appropriate statistical method for your model will be.