Second-half wagering is an under used betting opportunity that often can provide high-value wagers when you apply the proper analysis techniques during the game. Since almost every lined game provides a second half line, this is a widely available bet that can increase your winnings substantially if used correctly.
Bettors choose to bet second half lines for a variety of reasons. Some may want to hedge or middle an original bet. Perhaps they saw something during the first half that causes them to lean one way or another, such as an injury, foul trouble, etc. However, we tend to approach second half wagering in a very mathematical manner, with the basic idea being “all things regress to the mean” and that “mean” is the closing line. There are two methods that we tend to employ:
- Make a wager where the second half line gives value against the implied second half line (the closing line divided by two) AND the adjusted game line gives value against the closing line.
- Make a wager where the adjusted game line (the final game spread that equates to the second half line) falls within one standard deviation of the closing line.
IMPLIED SECOND HALF LINE AND THE ADJUSTED GAME LINE
In this instance, we’re attempting to find value in the second half line against the implied line combined with the adjusted game line against the closing line. Essentially, we assume a team will play around their average in the second half giving us an advantage on the line we’re taking.
An example would be this past Monday’s UNC Greensboro-Duke game. Duke closed as a 30-point favorite, which implies a line for each half would be -15. At halftime, Duke was leading 45-34 and the second half line was Duke -14, making the adjusted game line Duke -25. By taking this line we’re getting a point of value on the second half line based on the implied line and five points on the adjusted game line versus the closing line.
If we assume Duke plays around their closing line expectation, they cover the second half line. Based on the first half results, if they regress to the mean (i.e. play better than their underperforming first half), they will cover.
STANDARD DEVIATION AND THE ADJUSTED GAME LINE
When it comes to making mathematical analyses, is there a better place to turn than to the kids at Harvard? We consider this post from Harvard Sports Analysis blog to be both interesting and useful. It is worth nothing that the standard deviation doesn’t change that much throughout the season. (A quick aside on standard deviation: one standard deviation under normal circumstances will include about 68% of all results. You can read more about it here.)
That article shows that the standard deviation of college basketball games’ final results from the closing line is usually between 10 and 12 points.
This implies under a normal distribution around 68% of all college basketball final scores will be within 11 points of the closing line. Therefore, when we begin looking at second half lines we target positions where the adjusted line is more than one standard deviation away from the closing line. This means if the final score falls within one standard deviation, we win our second half bet.
On Monday, Portland played at Utah and closed as 3-point favorites. At halftime, the Pilots trailed 39-27. The second half line was Portland -4, making the adjusted game line Portland +8. This gave us 11 points of value against the closing line and if the final score fell within one standard deviation of the closing line, it would win. Portland ended up winning the second half 40-33, which resulted in a Utah 72-67 victory. That brought the final score back within one standard deviation of the closing line, and thus winning us our bet.
Portland’s second half line did not provide value against the implied second half line (-4 vs. -2), but the Pilots’ poor first half play justified the bet because they were likely to play much better in the second half as their play regressed toward the mean.
The above two approaches are by no means a “system.” They are merely the first steps to identify value in second half wagers. From here, we often build on this by looking at the following other aspects of the game:
- 3 PT %. Is the team that is outperforming the closing line shooting lights out compared to their average and their opponent’s defensive average? Is this likely to continue?
- FG %. Same as above, with one further note. If a team is shooting lights out from behind the arc, but has a poor overall FG%, this implies they are struggling to score and relying heavily on a hot streak that is likely to normalize in the second half. However, you do need to make sure this isn’t the teams M.O. by checking their 3PA/FGA. Florida, for instance, shoots a lot of 3s and makes a lot of 3s.
- Turnovers. Is the underperforming team turning the ball over a lot compared to normal? If so, is it because they’re playing a team who forces a lot of turnovers? You hope the answers are “yes” and “no” if you want to play the second half.
- FT Attempts. Same approach as turnovers.
- Foul Trouble. Does the underperforming team have someone they rely a lot on in foul trouble, causing them to underperform? If he stays out of trouble in the second half, taking a second half position could be optimal. This is tricky because if he picks up a quickie to start the second half, you could be behind the 8 ball.
We hope this gives everyone some insight into how to find value in the second half lines. We’ve found these to be a very successful approach to college basketball betting, and hope you are able to find similar success.
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