  We analyze cross-correlation between runs scored over a time interval in
cricket matches of different teams using methods of random matrix theory (RMT).
We obtain an ensemble of cross-correlation matrices $C$ from runs scored by
eight cricket playing nations for (i) test cricket from 1877 -2014 (ii)one-day
internationals from 1971 -2014 and (iii) seven teams participating in the
Indian Premier league T20 format (2008-2014) respectively. We find that a
majority of the eigenvalues of C fall within the bounds of random matrices
having joint probability distribution $P(x_1...,x_n)=C_{N \beta} \,
\prod_{j<k}w(x_j)| x_j-x_k |^\beta$ where $w(x)=x^{N\beta a}\exp(-N\beta b x)$
and $\beta$ is the Dyson parameter. The corresponding level density gives
Marchenko-Pastur (MP) distribution while fluctuations of every participating
team agrees with the universal behavior of Gaussian Unitary Ensemble (GUE). We
analyze the components of the deviating eigenvalues and find that the largest
eigenvalue corresponds to an influence common to all matches played during
these periods.
