The article discusses the accuracy of ESPN's fantasy football projections. The author, after a casual remark at work, delves into a data analysis to determine if ESPN's projections are biased. Using historical projection data and actual scores, the analysis reveals that ESPN tends to over-project points. However, when considering relative error, which accounts for the size of the projection, ESPN's projections appear accurate. The article concludes that while ESPN's average relative error is zero, they over-project 60% of the time, indicating a need to understand the underlying data distribution. The analysis was sparked by a workplace bet between colleagues, with the author's team at Datascope Analytics conducting the research.

Spiritbox, a band that has gained significant popularity following their debut album 'Eternal Blue', has been touring globally and impressing fans with their live performances. They released a three-track EP titled 'Rotoscope' earlier in the year. The band's guitarist, Mike Stringer, reflects on the past year, sharing his favorite albums and songs of 2022, as well as memorable moments from their tours. He highlights playing at Red Rocks as a standout experience and teases that Spiritbox will continue to write music and tour in 2023. The article also mentions that Spiritbox will be performing live for the first time in Australia at Knotfest in March 2023.

In the article 'Design for Augmented Intelligence', the authors discuss the importance of integrating human-centered design with big data and artificial intelligence. They argue that for AI to be truly effective and accepted, it must be designed to be empathetic and responsive to human needs. The article announces the acquisition of Datascope by IDEO to create D4AI (Design for Augmented Intelligence), which aims to make AI feel natural and augment human capabilities. The authors emphasize the need for interdisciplinary teams to work together and highlight the importance of designing data-driven interfaces that reflect human behavior. They also discuss the potential biases in data and the importance of human insight in creating meaningful AI systems. The article provides examples of how data alone can fail without human-centered design, such as the public health issue of lead in house paint in Chicago.

The article discusses the importance of correctly identifying problems in business to ensure that resources are not wasted on solving the wrong issues. It critiques the traditional define-plan-execute method of problem-solving, using Netflix's 2006 recommendation algorithm challenge as an example of a well-executed but misdirected effort. The article advocates for an iterative approach to problem-solving, where ambiguous problems are continuously redefined and tackled with fast, low-cost iterations. This method is likened to practices in various fields such as human-centered design, lean startup methodology, agile development, and the Deming wheel. The author's company, Datascope, applies this iterative process to data science and Big Data projects, emphasizing the importance of starting with the biggest problems and the smallest actionable steps.