Introduction to Sports Betting Models
In recent years, the rise of AI and the legalization of sports betting across most states has led to an influx of individuals creating their own sports betting models. This phenomenon is reminiscent of the early 2000s and 2010s, when everyone wanted to start making music after the internet made it easier to share their work. Now, it seems like everyone who has ever placed a wager is creating a sports betting model.
Getting Started
When starting out, it’s essential to stick to one sport to allow for more trial and error and to avoid overwhelming yourself. Building and maintaining a betting model requires an immense amount of time and/or skills with automation. Begin by assessing what stats you may want to incorporate into your model. It’s crucial to remember that simpler is often better. Using every advanced metric available may seem appealing, but it’s not necessarily the key to success.
From Stats to Projections
Once you’ve selected your stats, you need to turn them into a projection. This is where critical thinking comes into play. You must determine how your chosen stats correlate to points. For example, if you’re doing football, choosing a stat like QBR might be great for determining the best quarterback, but not so great for projecting a game. Consider using stats like points per play or points per drive, which can be more useful for game projections.
Opponent-Adjusting Your Data
One of the most critical aspects of creating a successful betting model is opponent-adjusting your data. This is what separates good models from those that simply use raw stats. Most people can plug in raw stats to make a quick projection, but opponent-adjustment is the key to making accurate predictions. To do this, you’ll need to organize your data effectively, which can be a daunting task.
Organizing Your Data
Getting organized is crucial for opponent-adjusting your data. There is no one-size-fits-all approach, so it’s essential to find a method that works for you. You can either opponent-adjust every game once you’ve established your baseline for how good each team is or take a team’s raw average stats and adjust it for the overall schedule to date. The first method requires more time and organizational setup, while the second method can be accomplished with a few columns on a sheet.
Automating Your Data Collection
Manually inputting data into your Excel or Sheets file can be time-consuming and prone to errors. To overcome this, you’ll need to find ways to automate your data collection. You can start by using simple tools like IMPORTHTML formulas in Excel/Sheets to pull in data from your website of choice. However, as you accumulate more data, you may need to switch to more advanced tools like Python or R. These platforms can seem intimidating, but with determination and practice, you can learn to use them effectively.
Monetizing Your Model
As you build your model and gain a following, you may be tempted to monetize your work. However, it’s essential to wait until you’ve accumulated a solid enough following to earn difference-making money. Early on, building a following is your currency. Provide great free value, build a following, and then you can try to cash in on your hard work. Remember, creating and maintaining a sports projection model is a marathon, not a sprint.
Conclusion
Creating a sports betting model can be a challenging but rewarding experience. By sticking to one sport, using simple stats, opponent-adjusting your data, organizing your data effectively, automating your data collection, and waiting to monetize your model, you can increase your chances of success. Remember, there is no “easy” button for creating and maintaining a sports projection model. It takes time, effort, and determination, but with persistence and practice, you can build a successful model that helps you make informed betting decisions.
