Predictive Cloud Computing with Big Data: Professional Golf and Tennis Forecasting [Application Notes]

Major Golf and Grand Slam Tennis tournaments such as Australian Open, The Masters, Roland Garros, United States Golf Association (USGA), Wimbledon, and United States Tennis Association (USTA) United States (US) Open provide real-time and historical sporting information to immerse a global fan base in the action. Each tournament provides realtime content, including streaming video, game statistics, scores, images, schedule of play, and text. Due to the game popularities, some of the web servers are heavily visited and some are not, therefore, we need a method to autonomously provision servers to provide a smooth user experience. Predictive Cloud Computing (PCC) has been developed to provide a smart allocation/deallocation of servers by combining ensembles of forecasts and predictive modeling to determine the future origin demand for web site content. PCC distributes processing through analytical pipelines that correlate streaming data, such as scores, media schedules, and player brackets with a future-simulated tournament state to measure predicted demand spikes for content. Social data streamed from Twitter provides social sentiment and popularity features used within predictive modeling. Data at rest, such as machine logs and web content, provide additional features for forecasting. While the duration of each tournament varies, the number of origin website requests range from 29,000 to 110,000 hits per minute. The PCC technology was developed and deployed to all Grand Slam tennis events and several major golf tournaments that took place in 2013 and to the present, which has decreased wasted computing consumption by over 50%. We propose a novel forecasting ensemble that includes residual, vector, historical, partial, adjusted, cubic and quadratic forecasters. In addition, we present several predictive models based on Multiple Regression as inputs into several of these forecasters. We conclude by empirically demonstrating that the predictive cloud technology is able to forecast the computing load on origin web servers for professional golf and tennis tournaments.

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