The paper introduces a new software tool that calculates a wide range of network indices, visualizes bipartite networks, and generates null models. The authors investigate the sensitivity of 26 network indices to network dimensions, sampling intensity, and singleton observations. They find that many indices are highly correlated and influenced by network dimensions and connectance. The study re-evaluates five common hypotheses about network properties using 19 pollination networks and three different null models. The results indicate that while some hypotheses hold up, others are largely explained by network size rather than ecological interrelationships. Specifically, the null model predictions for dependence asymmetry and robustness to extinction are opposite to current network paradigms. The analysis and the provided software enable ecologists to contrast their findings with null model expectations, separating statistical inevitability from ecological processes.The paper introduces a new software tool that calculates a wide range of network indices, visualizes bipartite networks, and generates null models. The authors investigate the sensitivity of 26 network indices to network dimensions, sampling intensity, and singleton observations. They find that many indices are highly correlated and influenced by network dimensions and connectance. The study re-evaluates five common hypotheses about network properties using 19 pollination networks and three different null models. The results indicate that while some hypotheses hold up, others are largely explained by network size rather than ecological interrelationships. Specifically, the null model predictions for dependence asymmetry and robustness to extinction are opposite to current network paradigms. The analysis and the provided software enable ecologists to contrast their findings with null model expectations, separating statistical inevitability from ecological processes.