Constructing a Sports Wagering Predictive Model: Suggestions, Strategies, and Guidance
The 2020s have become the era of AI and sports betting legalization across many states. With this new landscape, it seems everyone who's ever placed a sports bet is creating a sports betting model. This article covers common questions and advice for those who are new to the process.
Got the Betting Itch but Don't Know Where to Start?
Stick to one sport to avoid overwhelming yourself. Building and maintaining a betting model requires a considerable amount of time, skills with automation, and an intimate understanding of your sport. Assess the stats that could be useful for your chosen sport and don't rush to use advanced metrics. Remember, sometimes simplicity is key.
Turn Those Stats into Projections
Your first critical thinking step is to determine how the stats you've chosen link to scoring points. For example, if you're focusing on football, a stat like QBR might be great for identifying the best quarterback but not for projecting scoring because there's not a quantifiable correlation to points. Instead, consider statistics such as points per play or points per drive.
When Projections Don't Match the Market Line
If your projections deviate significantly from the market line, it's crucial to understand why. Opponent-adjusting your data can help you create a more accurate model. Think of this step as the "secret sauce" of sports betting projections. Remember, there's no right or wrong way to adjust your data; the most important thing is that you're organized and have a system that works for you.
Tips for Getting Organized
Getting organized is essential for seamless data manipulation. When you're starting, consider applying opponent adjustments to every game once you've established ratings for each team. For simplicity, you can also adjust raw averages for the overall schedule until you figure out how to use your own rating system.
Automate, Automate, Automate
One of the most significant obstacles in maintaining a model is keeping the structure, tools, and skills intact. Begin by utilizing tools like IMPORTHTML formulas to pull data without manually inputting it into your Excel or Sheets file. Eventually, you'll need to move on to more advanced tools like Python or R to handle larger volumes of data.
Don't Monetize Too Early
Finally, building a following is vital. Offer free valuable content to accumulate a solid following before attempting to monetize your model. It's a long-term game, so be patient and focus on providing solid, reliable predictions to attract followers.
- In the current era of AI and sports betting legalization, there's a trend of everyone creating their sports betting model, even for a single sport like college football or live betting.
- To transform your stats into projections, you need to understand how they link to scoring points, such as points per play or points per drive in sports like football.
- If your projections differ significantly from the market line, it's essential to analyze why, perhaps by opponent-adjusting your data to create a more accurate model.
- Organizing your data is crucial for seamless manipulation. Consider applying opponent adjustments to every game once you've established ratings for each team.
- To maintain a model efficiently, utilize tools like IMPORTHTML for data integration and eventually transition to advanced tools like Python or R for handling larger data volumes, while refraining from monetizing too early and focusing on providing valuable, free content.
