The increasing popularity of wireless networks has led to instances of high utilization and congestion, some of which have resulted in an interruption of network service. A thorough understanding of how IEEE 802.11 wireless networks operate is crucial to predicting and preventing future interruptions. There have been many studies performed on wireless networks. Of those that have captured data from the wireless side, most have used a form of wireless network monitoring known as Vicinity Sniffing (wireless sniffing from a location that is physically close to an access point to be in the broadcast range) as the primary means of capturing data. We believe that with recent advancements, SNMP is now capable of producing reliable results that were previously unattainable. We were presented with several obstacles in our studies, most of which are beliefs that SNMP is inadequate for monitoring IEEE 802.11 wireless networks. The claim is that SNMP provides either aggregated statistics or instantaneous values, and that it cannot report data on a per-device level, which is often desired so that individual details of a network"s performance may be analyzed. Although the data is aggregated over some length of time, recent advancements do in fact allow for per-device details. Because of this, we believe that these claims are no longer valid, and that they are hindering the use of a very versatile tool. This study is motivated by the iTiger project which is a research project located at Clemson University. A prototype system has been developed allowing fans attending home football games to interact with a set of web applications using 802.11 enabled smartphones. A driving requirement behind the work presented in this thesis was to develop a framework for monitoring and analyzing the underlying IEEE 802.11 network used by the iTiger system. The work presented is based on a set of controlled experiments conducted in the football stadium. The result of our study will be to show that the latest generation of wireless equipment can provide data that was once thought to be available only from wireless monitoring. Through our analysis, we will provide a proof-of-concept that SNMP is more capable than previously thought and that the results obtained from wireless networks are as accurate, and in some situations even more accurate, than those statistics acquired from using the techniques of Vicinity Sniffing.