In the past, when we have written about how to bet baseball, we explained how underdogs with high totals have been profitable for sports bettors, but until now had not offered any evidence to support this assumption. The theory is very basic: high totals lead to more unpredictability and that volatility benefits the team receiving plus money (i.e. the underdog).
To test this theory on how to bet baseball, we used our Bet Labs software to look through more than eight years of MLB betting data. We first chose to focus solely on underdogs by using the “Favorite/Dog” filter, and then continued by adding our “O/U” filter and steadily increased the total by a half-run starting at 6. Our belief was that as the total increased, we would see a constant increase in our return on investment (ROI).
The table below, which uses line data from Pinnacle, shows the record for all underdogs as the total escalates.
Outside of the decrease between 8.5 and 9 and 10.5 and 11, we noticed that both the winning percentage and ROI increased as the total became higher. In fact, simply betting every underdog in games where the total was at least 10 would result in a winning system. This is not a recommended betting system, but it does show a definitive edge for shrewd sports bettors.
Today, there are no games with a total of at least 10, however both the Blue Jays and Diamondbacks are worth monitoring as they are underdogs in games with a total of 9.5. Historically, games played at Coors Field, Fenway Park and Rangers Ballpark in Arlington have most frequently had a total of at least 10, so we would recommend keeping tabs on the Rockies, Red Sox, and Rangers, respectively.
Would you like to add more filters to this system? Schedule a live demo with our BetLabs manager and you can begin creating your own winning betting systems today.
Latest posts by David Solar (see all)
- NCAAF Game of the Week: Penn State vs. Wisconsin - December 2, 2016
- How Has Gronkowki’s Latest Injury Affected Patriots’ Super Bowl Chances? - December 2, 2016
- Sports Insights Podcast: Episode 17 (December 1, 2016) - December 1, 2016