  Once supersymmetry is found at the LHC, the question arises what are the
fundamental parameters of the Lagrangian. The answer to this question should
thereby not be biased by assumptions on high-scale models. SFitter is a tool
designed for this task. Taking LHC (and possibly ILC) data as input it scans
the TeV-scale MSSM parameter space using its new weighted Markov chain
technique. Using this scan it determines a list of best-fitting parameter
points. Additionally a log-likelihood map is calculated, which can be reduced
to lower-dimensional Frequentist's profile likelihoods or Bayesian probability
maps.
