Sports Betting Model Excel Template

Once I learned that Andrew Mack had begun work on the second volume of his Statistical Sports Models in Excel book series and that it would be published in a matter of months, I realised that I was yet to share my thoughts on his first instalment.

How To Build A Predictive Betting Model. Building a sports betting model can be difficult work. We won't lie to you. It can mean long hours of tediously entering data, sorting spreadsheets, setting up databases, testing, re-testing and re-re-testing. Sports Betting Excel Spreadsheet. Thread starter Masterz13; Start date Aug 15, 2014; Tags accumulate accumulator bet excel sports M. Masterz13 New Member.

This is a book review that should have been published long ago. Not because I read volume one back in August of last year, but because of the valuable lessons it can teach bettors and the more people that are aware of those lessons, the better.

One of many ways to bet

Although many bettors don’t like to believe it, there is no goose that lays the golden eggs in sports betting. There are various different ways to approach betting on sports and each have their own merits and potential pitfalls. In his book, Andrew Mack focuses on one particular approach that can lead to success when the required time and effort is put in to get the desired results.

The world of data analytics and modelling in sports betting is nothing new. However, breaking down the odds in a betting market through analysis of data sets and using simulations and models to predict future outcomes has very much taken over the traditional handicapping we might have seen at sportsbooks less than a decade ago. Andrew even references Pinnacle’s own Marco Blume and the fact that he’s talked about how our traders are using R and Python for pricing and trading.

• Introduction to Sports Gambling 1.1. Similarities and Differences Compared to Traditional Gambling Sports gambling is a form of betting similar to traditional probability games such as roulette, dice, or cards. The result of a sports bet is settled based on the outcome of a sporting event on which none of the betting parties has any.
• The shortest 'cut' would be to purchase my betting models and watch my videos, however for those that are on a budget (I hear ya!), don't expect to magically wake up with the ability to build a sports betting model. First, you should do the following: Learn basic mathematics and how statistics work.
• Discount Codes Sports Betting Excel Sheet Template Comparison,Budget Sports Betting Excel Sheet Template Cons.

Much like building models and setting your own odds to compare against the market is one of many ways to bet, there are countless methods and programs to use within the wide-ranging term of sports modelling. As the title suggests, this book focuses on Excel rather than a detailed analysis of other programming languages like the aforementioned R and Python.

Honing in on one specific language may alienate those that have already discovered they are better suited to alternative options, but it also allows the book to delve straight into the real detail without generalising. There’s nothing more off-putting for a reader, especially a novice in this field like myself, than having to wade through materials or examples that aren’t applicable and can’t be used to help improve your understanding.

Don’t expect a guide on how to win in sports betting

It is an outlandish claim for any book to say it offers a simple solution to winning in sports betting. However, the problem we have is that there are so many people out there wanting to believe it’s possible - and this makes books that appeal to a get rich quick mentality possible and it’s why they are probably some of the best-selling books out there.

Statistical Sports Models in Excel is at the opposite end of that spectrum. It is laden with warnings about how difficult it is to achieve positive expected value with your bets and that it will likely take a lot of mistakes and a lot of failure before you even get close to that point.

There are no convoluted sentences, concepts are communicated clearly and for each example used there is a thorough-guided process with additional visual cues.

I think what Andrew’s book offers is a big step in the right direction for breaking down something that can often be quite daunting to bettors. Many people will be so put off by the technical jargon and lack of user-friendly interfaces for a lot of the necessary software or applications that they won’t even begin the journey of modelling in sports betting.

What this book does is open the door to those with an interest who haven’t quite made the jump to getting their hands dirty yet, or those who have tried but require additional help.

The fact that Andrew is happy to give this information away shows that there is little to no value in betting with the actual examples shown. There is value, however, in learning about the benefits of sports modelling, where to access data, how to use it and where these newfound skills can take you (as well as how much additional work is required).

An important word of warning

It is important for those interested in reading this book that, as Andrew states in the very opening, sports betting is “fraught with difficulty”. This obviously means you should expect challenges and periods of difficulty if you hope to reach the end goal of achieving consistent profits.

This book is certainly a great place to start and while the level of complexity does follow a natural progression through the book so as to not put off the reader as they develop their skillset, it will be quite dense and require a bit of hard work to get through at points. I think you’ll be hard pressed to find any literature on this subject matter that doesn’t feel like that in parts.

The key to enjoying Statistical Sports Models in Excel is to treat it as an exercise book or textbook you might find in school. It will take work to get through it and when things don’t quite click, it might be best to take a break rather than ploughing through. It is worth persevering though and because it feels more personalised as a reader, it makes it much easier to stick with compared to the dull equivalents that might be handed out in class.

The key is in the simplicity

While I feel it is worth warning potential readers about the complexity of a book like this, it has to be said that keeping it as simple as possible is one of its standout features. There are no convoluted sentences, concepts are communicated clearly and for each example used there is a thorough-guided process with additional visual cues.

This focus on simplicity doesn’t hinder the breadth of sports that can be covered or the different models that are shown within Statistical Sports Models in Excel either. This approach also allows the reader to actually use the book as a workbook and while I don’t bet on a regular basis, I still found myself reading along with Excel open on my computer to see how easy it is to implement the teachings.

Statistical Sports Models in Excel is laden with warnings about how difficult it is to achieve positive expected value with your bets and that it will likely take a lot of mistakes and a lot of failure before you even get close to that point.

The text is cleverly structured and formatted to speak to the reader as they develop as a modeller. Only once you’ve got through the introduction that includes a walkthrough for setting up Excel and utilising the available add-ons (some are free and some come at a cost) and have your “Excel modelling toolbox” can you begin to look at working on actual models.

Excel Betting Spreadsheet

By the time you’ve got to trying out a Game Scores Standard Deviation Model, the earlier work on the Bradley Terry Model and Team OLS Optimised Rating (TOOR) model make the process much more straightforward. This isn’t just because of the similarities between these models, but the fact that the basics are covered first and with each step throughout the book do you build on your knowledge.

Of course, building these models is only one small step towards the end goal for the majority of people reading this. Developing your skills and building new models with other data-sets is needed to take things to another level, but starting out with a simple approach to building the foundations will certainly stand the readers in good stead.

I would strongly recommend anyone who finds themselves as an observer in conversations about modelling in sports take the time to read Statistical Sports Models in Excel. It’s benefits will most likely become even more apparent if you take a practical approach and follow the book as a guide. I, for one, am definitely looking forward to volume two in this series.

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

Excel 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

Using Excel For Sports Betting

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.

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.