The Texas Sharpshooter Fallacy

Alias: The Texas Sharpshooter Effect*

Taxonomy: Logical Fallacy > Informal Fallacy > Non Causa Pro Causa > The Texas Sharpshooter Fallacy


…[T]he epidemiologist Seymour Grufferman coined the term “Texas sharpshooter effect.” Stand way back and blast the side of a barn with a shotgun and then find some holes that are crowded together. Draw a circle around them and you have what looks like a bull’s-eye.*



The Texas sharpshooter is a fabled marksman who fires his gun randomly at the side of a barn, then paints a bullseye around the spot where the most bullet holes cluster. The story of this Lone Star state shooter has given its name to a fallacy apparently first described in the field of epidemiology, which studies how disease spreads in a population.*


Each year…epidemiologists regularly hear from people worried that their town has been plagued with an unusually large visitation [of cancer cases]. … The Erin Brockovich incident, one of the most famous, is among the many that have been debunked. Hexavalent chromium in the water supply of a small California town was blamed for causing cancer, resulting in a $333 million legal settlement and a movie starring Julia Roberts. But an epidemiological study ultimately showed that the cancer rate was no greater than that of the general population. The rate was actually slightly less.*


This fallacy occurs when someone jumps to the conclusion that a cluster in some data must be the result of a cause, usually one that it is clustered around. There are two reasons why this is fallacious:

  1. The cluster may well be the result of chance, in which case it was not caused by anything.
  2. Even if the cluster is not the result of chance, there are other possible reasons for the clustering, other than the cause chosen. For instance, if a disease is contagious, it may be clustered around a carrier.

At best, the occurrence of a cluster in the data is the basis not for a causal conclusion, but for the formation of a causal hypothesis which needs to be tested. Patterns in data can be useful for forming hypotheses, but they are not themselves sufficient evidence of a causal connection. In short, correlation is not causation.


This fallacy lives up to its striking name because the Texas sharpshooter takes a random cluster, and by drawing a target onto it makes it appear to be causally determined, as if the Texan were shooting at the target. Similarly, when looking at data, there is a danger of jumping to a conclusion that a random cluster is a causal pattern. Without further testing, such a conclusion is seldom if ever justified.

* George Johnson, "Cancer Cluster or Chance?", Slate, 3/19/2013