Author Archives: Brendan Kent

Sports Analytics 101 is a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. Over the previous six posts, I introduced a “The Metric Framework,” a framework for thinking about an individual sports analytics metric. Here, I’m going to apply theContinue reading “Sports Analytics 101: Metric Framework Examples”

Sports Analytics 101 is a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. In an earlier post, I introduced a framework for thinking about an individual sports analytics metric. This framework is essentially mental “paperwork” to fill out whenever youContinue reading “Sports Analytics 101: Blind Spots”

Sports Analytics 101 is a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. In an earlier post, I introduced a framework for thinking about an individual sports analytics metric. This framework is essentially mental “paperwork” to fill out whenever youContinue reading “Sports Analytics 101: Adjusting for Opportunity”

Sports Analytics 101 is a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. In an earlier post, I introduced a framework for thinking about an individual sports analytics metric. This framework is essentially mental “paperwork” to fill out whenever youContinue reading “Sports Analytics 101: Productivity vs. Style”

Sports Analytics 101 is a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. In an earlier post, I introduced a framework for thinking about an individual sports analytics metric. This framework is essentially mental “paperwork” to fill out whenever youContinue reading “Sports Analytics 101: Descriptive vs. Predictive”

Sports Analytics 101 is a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. When using the metric framework (introduced in the previous post) to analyze a metric, one of key things we need to establish is whether a metric,Continue reading “Sports Analytics 101: Facts and Proxies”

Sports Analytics 101 is a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. Sports analytics revolves around metrics: the numbers that go into a piece of analysis, and the numbers that come out on the other side. In fact, sportsContinue reading “Sports Analytics 101: A Framework for Metrics”

Welcome back to Sports Analytics 101, a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here. Thus far, we’ve covered analytics use cases for two key stakeholders: teams and leagues. In this installment, we’ll look at use cases for the media.Continue reading “Sports Analytics 101: Media Use Cases”

Welcome back to Sports Analytics 101, a series of blog posts outlining the core concepts behind sports analytics in non-technical terms. You can find all available installments in the series here.  In the previous two posts, we covered the three categories of analytics use cases for teams: in-game strategy,  player personnel strategy and sports science.Continue reading “Sports Analytics 101: League Use Cases”