• Making A Sports Betting Model In R
• How To Build A Sports Betting Model Reddit
• How To Make A Sports Betting Model In Excel
• Excel Sports Betting Model

Simple step-by-step guide including example spreadsheet on how to build a simple sports betting model. The Handicapper web app - For smart bettors. Create accurate, data-driven projections for MLB, NBA, NFL, NHL and EPL matcups. The Handicapper - The tool for the smart sports bettor. Major US Sports. This is something that public/square bettors are very poor at figuring out, leaving a lot of value on the table in the betting market. Much like a player projection system, our model identifies a 'true' performance level for players and projects games accordingly. You expressly understand and agree that Sports Model.

How do you build a sports betting model? What steps are involved? What do you need to consider? Follow these steps to build your own quantitative model, and take your betting to the next level.

What is a betting model?

In it's simplest form a sports betting model is a system that can identify unbiased reference points from where you can determine the probability for all outcomes in a particular game.

The model will ultimately be able to highlight profitable betting opportunities, by judging a team's true ability more accurately than a bookmaker.

However, building a sports betting model can be difficult and time consuming. There are various instructions and orders advised for you to follow when creating a model, which can complicate the process.

With that said, once you have created a successful betting model, it can show you opportunities that the general betting public simply wouldn't consider.

Let's begin.

For this example we use an approach similar to the Actuarial Control Cycle – a quantitative risk assessment employed by insurance companies. There are five main features:

• Defining the problem
• Building the solution
• Monitoring results
• Professionalism
• External forces

Step 1: Specify the aim of your betting model

This appears simple, but many sports bettors miss the point their betting model is trying to accomplish.

Once you have created a successful betting model, it can show you opportunities that the general betting public simply wouldn't consider.

Without an aim you could be overwhelmed with numbers and lose focus of your overall goals.

Although you may argue you can get the data first to see if there are any patterns, this would still need to be tested against a number of hypothesis, each with a different aim.

Therefore starting with a specific, rather than a generic aim, is strongly recommended.

Step 2: Select the metric

The next step is to formalise your investigation into numerical form by selecting a quantifiable metric.

These first two steps relate to defining the problem stage of the Actuarial Control Cycle.

Step 3: Collect, group and modify data

Every model needs data so you can integrate it into your algorithm. There are two ways of collecting data – by yourself, or by using other published data online.

Luckily, there is a plethora of data available on the Internet, some of which is free, while some websites offer a paid service.

Once you have the data, you may realise that there are queries that need to be taken care of.

If we are looking at Premier League teams for instance, should you consider all matches or just their league games? It's possible to make adjustments if the team in question had players missing, or had a mid-week Champions’ League clash.

This is where you can exercise your judgement, determined by what your aim is.

Step 4: Choosing the form of your model

This is where the mathematics comes into play given there are so many models to choose from or invent.

There is a plethora of data available on the Internet, some of which is free, while some websites offer a paid service.

We have proposed a number of models in the past and they can be as complex or as simple as you wish. Our recommendation is not to overcomplicate.

This step can be interchanged with step 3 as the data may lead you to use a particular model, or a particular model may require specific data.

Step 5: Dealing with assumptions

Each model will have a number of assumptions, and you should be aware of their limitations. You may forget to do this, but it's absolutely vital.

For example a significant contributor to the financial crisis in 2007-08 was the misuse of derivatives caused by a misunderstanding of assumptions in contracts such as Collateralised Debt Obligations and Credit Default Swaps.

Previously in this article we highlighted how averages and standard deviations assume events are normally distributed. This for example would need be tested.

Step 6: Build the sports betting model

The next step is to actually build the sports betting model. There are numerous tools to use including online calculators, Excel, MatLab, Java, R programming and VBA.

You don’t have to be a wiz at programming to build a sports betting model, but the more you understand the functionality, the better equipped you will become when testing and analysing the data.

Step 7: Test the model

You don’t have to be a wiz at programming to build a sports betting model, but the more you understand the functionality, the better equipped you will become when testing and analysing the data.

It's paramount that you test the efficiency of any sports betting model to understand how sensitive it is to the results.
In any case the results of the model may lead us to reconsider any of the previous steps.

The key question as always is whether or not the model is making a profit? Therefore you’d need to test that – leading you to running through the cycle again.

Step 8: Monitor results

Assuming that an adequate model has been built and tested, it needs to be maintained as time progresses. This leads us back to the starting point – defining future aims.

Applied knowledge

Understanding the processes involved is paramount when learning how to build a sports betting model.

Quantitative modelling isn’t just about taking a model and applying it, there are a number of processes – not necessarily in the order stated – which should be completed.

Following this process won't guarantee a profit-making model, but it will ensure you are considering the fundamental aspects that are needed to build a new sports betting model.

For an example of how to build a betting model, click here.

Making A Sports Betting Model In R

Dominic Cortis is a lecturer with the Department of Mathematics at The University of Leicester; and an assistant lecturer at The University of Malta. He is an associate actuary and his research focuses on sports analytics as well as financial and betting derivatives.

To make money betting on sports is possible, but requires discipline, practice, and understanding of odds and sportsbooks. The best way to illustrate what is required is to show the numbers behind becoming a successful sports bettor. In this article, we will take a look at a simulation that shows 10,000 simulated bets of $110 placed on -110 odds. We do this using the spreadsheets linked here: Excel, OpenOffice.

Listed along the top of the spreadsheet are percentages between 50 and 60%. You can focus in on the winning ratio you expect to attain. These numbers weren’t chosen at random. Because -110 is generally the odds that imply a probability winning 50% of your bets, this is your starting point as a sports bettor. 60% is about the highest winning percentage you can expect over time in sports betting. If anyone ever tells you they pick winners over time more than 60% of the time, they are either trying to get money out of you or they are deluding themselves. Run, don’t walk. A reasonable goal to make money betting on sports is 56-57%.

Below is a sample view of the simulation:

The first thing to notice is is the red “Expected Winnings” line. This line isn’t simulated. It is purely the math behind the expected outcome of these bets at the various outcomes. For example, a 54% bettor can expect to win 5,400 bets, winning $100 on each bet (remember, the -110 odds), meanwhile losing 4,600 bets costing $110 per time. That is going to win you $34,000 on average BUT that isn’t guaranteed to be the case. In betting there is volatility. That is where the simulated blue line comes in.

How To Build A Sports Betting Model Reddit

Because it is a simulation based on random numbers and the winning percentage, there is what we call volatility in the outcome. You see, over time the simulation should approach the red line, but in reality it is never going to be perfect. In a million bets…a billion…there is still going to be volatility. That is why increasing your winning percentage, even by a fraction is vital to make money betting on sports.

How To Make A Sports Betting Model In Excel

You’ll notice a very important point in the red line at 52.4%. This is the most important number for sports bettors. This is the break even point where you break free of the sportsbooks juice or vig, and start making profit. It doesn’t sound too hard, but as you can see, each fraction of a percent above that point means less chance that volatility is going to adversely affect the outcome and more profit.

Excel Sports Betting Model

Once again here are the links to the simulated spreadsheets: Excel, OpenOffice. I invite you to download them and run through some simulations by pressing CTRL-Shift-F9, which will make the blue line shift around.

Get used to fighting for every percent. Get used to fighting for every half-point in the spread. Get ready to fight for every fraction in the odds. In my articles, I am going to get you as close to 52.4% as I can. To make money sports betting, the rest is going to be up to you.