Texas Sharpshooter Fallacy

Drawing a target around bullet holes after shooting and claiming you hit the bullseye—finding a pattern in random data and then constructing a hypothesis to explain it as if you'd predicted it. A company that happens to succeed in three adjacent markets constructs a narrative about its 'adjacency strategy.' A fund that happens to outperform for three years constructs a story about its 'unique methodology.' Cancer clusters that appear on a map are post-hoc circled and attributed to local causes that may not exist. The Texas Sharpshooter Fallacy is the narrative fallacy applied to pattern detection: the pattern is real but the causal story is invented afterward.

When to use it

When impressive patterns are discovered in historical data; when success narratives are being constructed from coincidental clusters; when data mining produces 'insights' that haven't been validated; when the distinction between prediction and post-hoc explanation matters.

How it can help

For any pattern you discover: ask 'did I predict this pattern BEFORE seeing the data, or did I find it AFTER?' Patterns discovered after looking at data are hypotheses to be tested, not conclusions to be acted on. The correction: (1) Separate hypothesis generation (finding patterns) from hypothesis testing (validating them on NEW data). (2) Account for multiple comparisons—if you look at enough data points, some will cluster by chance. (3) Demand out-of-sample validation before building strategy on any discovered pattern.