In 2010, we started our journey by only covering the NBA from our reference website NBAstuffer for a little group of analysts who were in need of data. Throughout the years, our users have encouraged us to extend to other sports. This is why we have rebuilt our platform under the BigDataBall brand in 2014. We have added WNBA and NFL in 2017, MLB in 2018, and NHL in 2019. If you want to vote for a new sport, please do so.
The Business Model
BigDataBall aims to help individuals who want to analyze sports data without coding skills. Given limited availability and lack of collection time, it is a struggle to access easy-to-manipulate, cleaned-up, and enriched datasets. We run a crowd-sourced model where the collected data is being moderated through a couple of processing/analysis software in which we keep investing a significant amount of time and effort to develop and maintain a platform that enables contributing partners to collaborate.
Data is then getting enhanced with proprietary information such as rest-days/schedule/lineup/efficiency analyses. External datasets such as betting odds/movements, daily fantasy sports salaries/positions are also included to diversify the data points for our team/player/play-by-play, and DFS users who extract value, insight, and competitive edge from the sports data.
All datasets are being pushed into the validation processes where the errors are corrected to make sure that the output is accurate and complies with official data.
As we tried to give a brief regarding how we work, it would not be fair not mentioning that we provide a fast responding email support service to ensure your peace of mind. You will get a response within a 12-hour window.