The Poisson distribution is a term borrowed from statistical analysis, a way for mathematicians to compute the probability of the highly improbable. The typical use of the distribution is in broad based surveys that attempt to discover the possibility of a rare event happening-like, say, a no-hitter in baseball.
How rare is a no hitter? Well, pitcher Nolan Ryan is the undisputed king in this category. Ryan played in a major league record 27 seasons (Mets, Angels, Astros and Rangers from 1966-1993) and managed seven no hitters along the way. And his total is three more than the next closest contender.
So considering the rarity of the event, using statistics to predict such a thing seems no small task, but actually-according to recent work done by mathematicians at West Point-the Poisson distribution works quite nicely in this kind of prediction.
Also known as "the law of large numbers," the Poisson distribution has been used to determine everything from how diseases spread through populations to how many insect body parts are likely to turn up in a randomly selected candy bar. Truns out, applying it to baseball is not too big of a deal.












