Today at 4:00 (EST) Benjamin Alamar, author of Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makerswill take part in #cloudchat to discuss how Big Data, the cloud, and analytics are changing sports. Among the other guests will be Jon Wertheim, Sports Illustrated and Devin Pleuler, an advanced data analysts at Opta.

For the time being, you can read an interview with Alamar recently did with the Georgetown Sports Analysis, Business, and Research Group. In the interview, Alamar talks about how he got his start as an analyst for the Oklahoma City Thunder, how analysts balance the data with the many uncertainties in analysis, and how sports analytics can be applied to other fields.

Alamar also explains the importance of context in analyzing data:

Context for metrics is key to properly assessing what information the metric is conveying as well as presenting the metric in an effective manner for decision makers. The first step is for analysts to understand the processes that create the data that they are using. A quarterback’s passing data, for example, is the result of the efforts of 22 players on the field and the schemes outlined for them by their coaches. The analyst has to consider this carefully when building a metric that claims to measure a QB’s abilities. When working with Dean Oliver at ESPN on their QBR, we worked to first put each play in context of the situation (down, distance to go, yard-line etc.) and then, as much as possible, separate the efforts of the QB from all of the other factors that create the result of a play. Building models like those that create the QBR requires an understanding of the sport so the analyst can identify the factors that lead to any particular result so they are measuring as precisely as they can given the data available, what they really intend to measure.