  Analyzing football score data with statistical techniques, we investigate how
the not purely random, but highly co-operative nature of the game is reflected
in averaged properties such as the probability distributions of scored goals
for the home and away teams. As it turns out, especially the tails of the
distributions are not well described by the Poissonian or binomial model
resulting from the assumption of uncorrelated random events. Instead, a good
effective description of the data is provided by less basic distributions such
as the negative binomial one or the probability densities of extreme value
statistics. To understand this behavior from a microscopical point of view,
however, no waiting time problem or extremal process need be invoked. Instead,
modifying the Bernoulli random process underlying the Poissonian model to
include a simple component of self-affirmation seems to describe the data
surprisingly well and allows to understand the observed deviation from Gaussian
statistics. The phenomenological distributions used before can be understood as
special cases within this framework. We analyzed historical football score data
from many leagues in Europe as well as from international tournaments,
including data from all past tournaments of the ``FIFA World Cup'' series, and
found the proposed models to be applicable rather universally. In particular,
here we analyse the results of the German women's premier football league and
consider the two separate German men's premier leagues in the East and West
during the cold war times and the unified league after 1990 to see how scoring
in football and the component of self-affirmation depend on cultural and
political circumstances.
