We present an Outlier Detection using Indegree Number (ODIN) algorithm that utilizes k-nearest neighbour graph. Improvements to existing kNN distance -based method are also proposed. We compare the methods with real and synthetic datasets. The results show that the proposed method achieves resonable results with synthetic data and outperforms compared methods with real data sets with small number of observations.