What is a Sports Betting Model? How to Build and Use One

Sports betting is more than having hunches. Learn how to build a sports betting model that identifies unbiased probabilities, removes emotional bias, and finds profitable opportunities systematically.

Hopefully by now you have figured out that sports betting is a lot more than having hunches about a specific team that is going to have a "big night."

In fact, if that is how you are sports betting, the books probably love having you as a customer.

There is nothing wrong with betting like this—especially if your aim is to just have some fun and maybe hit a lottery ticket pick.

However, if your aim is to make money over a period of time, you need to be using a sports betting model to identify the most profitable betting opportunities, not just those that you want to bet on.

What is a Sports Betting Model?

A sports betting model is a system that can identify unbiased probabilities so you can determine the most likely outcomes in a game.

In other words, it takes the bias out of your picks and boils them down to numbers.

It doesn't care that you KNOW the Chiefs are gonna win this year because of a dynastic mission. The model is based only on the data that has been input into it and cross-referenced with other lines.

7-Step Process to Build a Betting Model

Step 1: Specify the Goal of Your Model

This seems obvious but the goal cannot be something as broad as "make me more money." The goal has to be based around numbers and have a narrow focus.

Consider questions like:

• What sport is this model for?
• What advantages am I looking for?
• What is my tracking time for this model? (a week, a month, a year?)

Starting with a specific focus is already putting you on the right track to creating a successful sports betting model.

Step 2: Select Your Metric(s)

This simply means choose the metric or metrics that you are going to use in your betting model.

Some examples of metrics you could use are:

• Positive Expected Value
• Closing Line Value
• No-Vig Odds
• History Against the Spread

As in everything, some metrics are going to be better than others. If everyone knew a "magic metric" that guaranteed profit, sports betting wouldn't exist. There is no magic bullet.

Step 3: Collect and Modify Data

Now you have decided what the goal of your model is and what metric(s) you are going to use. The next step is to gather the data!

There are two ways to go about this:

Collect It Yourself

If you have the time and drive, you can take a look at all of the lines across books and compare them to each other, calculate whatever metric you have decided to go by, and input it into an Excel spreadsheet.

There is absolutely nothing wrong with this and, honestly, more power to you if this is the route you choose to go!

Use Data Available Online

Some data will be available for free such as:

• Scores and odds
• Line movements
• Historical team data
• Public betting percentages

Other data is available but has to be paid for. Tools like FairOdds Terminal provide:

• Arbitrage opportunities with alerts
• +EV bets with alerts
• Pre-computed fair lines to compare bookmaker lines
• Automated bet tracking

Step 4: Choose the Type of Model

Now it is up to you to decide what type of model you want to use. Sports betting models can be incredibly complex or surprisingly simple.

In the end it is really all about what works for you as long as it DOES work.

Here are some examples:

Regression Analysis

Regression analysis attempts to determine the important factors that can determine the outcome of an event.

Famous examples:

• NFL regression: The league concluded that passing efficiency had the highest effect on game outcomes. Over 75% of past Super Bowl champions had passing efficiency of more than a yard per attempt.
• Moneyball: Regression analysis gave Billy Beane a successful MLB strategy focusing on undervalued metrics.

Kelly Criterion

The Kelly Criterion determines bet sizing based on your edge. Bet = Edge ÷ Odds.

Use fractional Kelly (quarter or half) to avoid over-betting since we can't exactly quantify our edge in sports.

Martingale & D'Alembert

These systems involve progressively betting more if your bets lose.

The danger: You can hit a rough patch and the amounts you have to start betting get high quickly. Requires large bankroll.

Step 5: Build the Model

There are a variety of ways to build your sports betting model. The most important part is to keep track of your bets.

To do this you can:

• Use Excel or Google Sheets (free)
• Use betting model software
• Use FairOdds Terminal's built-in bet tracker

Track:

• All bets and amounts
• Which bookmaker you bet at
• The line you got
• Type of bet
• Closing line value
• Return on investment

Step 6: Test the Model and Monitor Results

You want to know if the model works! Test your model out for a week to a month and see if you are generating profit.

If not, you may need to re-evaluate your model. It could be:

• Your metrics are not good metrics to use
• Your bets are inconsistent
• Your bigger bets are the ones that are not hitting

Step 7: Win Money

Once your model is tested and verified profitable:

1. Stick to the model consistently
2. Don't deviate based on gut feelings
3. Continue tracking all results
4. Adjust only when data suggests improvements

Combining Models for Best Results

Many of these models can be combined. I always suggest combining:

• One "how much do I bet" model (Kelly Criterion)
• One "statistical" model (regression, EV-based)

The only guaranteed thing is you are going to lose some bets. The point of the model is to give you a statistical edge on the books as well as ensure you are betting amounts that add up to profit over time.

Frequently Asked Questions