One of the biggest challenges in the RoboCup Soccer Standard Platform League (SPL) is autonomously achieving and maintaining an accurate estimate of a robot’s position and orientation on the field. In other robotics applications many robust systems already exist for localization such as visual simultaneous localization and mapping (SLAM) and LIDAR based SLAM. These approaches either require special hardware or are very computationally expensive and are not suitable for the Nao robot, the current robot of choice for the SPL. Therefore novel approaches to localization in the RoboCup SPL environment are required. In this paper we present a new approach to localization in the SPL which relies primarily on the information contained within white field markings while being efficient enough to run in real time on board a Nao robot.