The Zig-Zag theory for handicapping the NBA playoffs has steadily gained in popularity over the last few years. The concept is appealing: bet on teams coming off a loss in the playoffs to cover the point spread.
It is pretty easy to fill in the narrative to justify the strategy. Losing teams have more resolve to bounce back from a loss. Winning teams may have just a little less urgency to win again. And, at one point, teams coming off a playoff win in the series may become overvalued in the next game if the betting public becomes too enamored with the Recency Effect.
But the point spread is the run — and the great equalizer. If the betting public begins to ignore the Recency Effect and begin banking on the Zig-Zag theory, the oddsmakers will adjust with worse lines on the team coming off a loss. Every half-point line moment matters as it decreases the win probability of that side covering the point spread. As more and more bettors employ the Zig-Zag approach, the value in the system will likely decline. I wonder if there will become a time where the betting value will become to fly the contrarian flag and bet against the zig-zag?
The most important thing to consider when assessing past data is that it must be analyzed in relation to the point spread situation in question. Maybe a home favorite coming off a point spread loss by double-digits have covered the point spread in 28 of these last 32 situations — but if that home favorite is laying, say, 100 points, then they are not going to cover the point spread no matter who shiny the data mined angle is. Obviously, this example is exaggerated, but I do so to make this observation: there is a threshold as to when a past truth derived from empirical data will stop being a truth in the future given the changing expectations of the situation as demonstrated by the fluid point spread.
Let’s look at how the Zig-Zag theory has done so far through four games in the first round of the NBA playoffs. Overall, teams coming off straight-up losses in the previous playoff game this season have then covered the point spread in 11 of the 24 games. Or, put another way, Zig-Zag is 11-13 ATS in Games Two, Three, and Four this postseason. Sample size is always a consideration, but zombie auto bet Zig-Zaggers have not made money in these playoffs.
Let’s look at the game-by-game breakdowns. In Game Two, teams off a straight-up loss in Game One are 4-4 ATS. In Game Three, teams off a straight-up loss in Game Two are 3-5 ATS. In Game Four, teams off a straight-up loss in Game Three are 4-4 ATS.
In general, I am highly skeptical of silver bullet evidence to inform a situation in which to invest. The fluidity of the market makes such evidence short-term, at best. My handicapping approach is to assess and then analyze a wealth of evidence utilizing several different methods and approaches. My Reports are long to communicate this investment. Zig-Zag is certainly something I look at. I find the theory carries more weight when it combines with other intangibles such as team trends that help to expose a personality of a team.
I will continue to assess how the Zig-Zag theory is working as the NBA playoffs move forward. Sharp bettors should already be exerted caution when considering the system. Sometimes the best answer to a Zig is to just pass. The day may come sooner rather than later that the expectation of a Zag from the betting market may create value to keep on Zigging.
Best of luck — Frank.