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P3, a sports performance company, employs a multidisciplinary team of sports scientists, biomechanists, performance coaches, and strength coaches. Each discipline has its own jargon and perspective on data, which initially caused communication challenges. Dr. Marcus Elliott prioritized three strategies to overcome this: aligning the team around a single goal (“to make athletes’ lives better”), limiting technical jargon so everyone can understand the data, and providing ongoing cross-disciplinary education. By creating a shared language, team members could collaborate more effectively, ensure analytics informed actionable decisions, and enhance athlete outcomes. According to Shields in Integrating Analytics in Your Organization: Lessons from the Sports Industry, what is the primary benefit of establishing a common language for analytics within an organization?

Which term describes the process that focuses on analyzing written feedback, such as emails, surveys, chatbots, reviews, forums, and social media posts, to understand fan opinions and improve digital experiences and engagement?

According to Rasmus Ankersen in his TED talk “What Football Analytics can Teach Successful Organizations”, what key discovery about football performance can organizations apply to improve their decision-making?

A popular online gambling influencer has built a following by predicting WNBA player performance based on assumptions about their menstrual cycles. He analyzes stats such as field goal percentage and plus/minus over what he believes to be 24–38-day cycles, despite having no confirmed medical information from the athletes themselves. While he claims his model increases fan engagement, sports medicine experts note the approach is pseudoscientific, invasive, and rooted in sexist assumptions. WNBA advocates warn that such practices can reinforce harmful stereotypes, impact perceptions of women’s athletic performance, and create ethical concerns around privacy and data misuse. What is the primary ethical issue raised by this betting strategy?

After seeing viral clips of blind fans using their hands to follow a soccer match, the founders of OneCourt, Field of Vision, and Touch2See realized there was an untapped market. They used real-time sports tracking data to build tactile devices that let visually impaired fans feel ball movement, receive vibration cues for key plays, and follow games independently. As more leagues adopt advanced tracking systems, these companies see growing demand from stadiums and home viewers. Their success shows how innovators can use data and technology to serve audiences that traditional sports products have overlooked. What does this example best show about using data and technology in sports?

According to the MIT Sloan podcast episode “So, Do Analytics Actually Work?”, what is the primary way analytics contributes to sports?

Right before a UFC bout in Las Vegas, betting-monitoring firm IC360 detected a sharp and unusual shift in wagering patterns: Isaac Dulgarian’s odds suddenly dropped, and a surge of bets came in on his opponent winning in the first round. Dulgarian then lost quickly, triggering an investigation. UFC, which relies on real-time betting analytics to flag suspicious activity, immediately contacted the FBI. The incident follows several high-profile cases across sports in which players faced penalties for manipulating their performance to influence betting outcomes. What does this case most clearly demonstrate about the relationship between sports betting and data analytics?

For decades, Major League Baseball evaluated hitters primarily by batting average, rewarding players who accumulated lots of singles and made frequent contact. But when front offices—driven by the sabermetrics movement—shifted toward on-base percentage (OBP) as a key metric, a new type of hitter began to thrive. Players who walked often, demonstrated plate discipline, and forced long counts became far more valuable, even if their batting averages were modest. A similar pattern emerged in the NBA. As analytics emphasized the value of three-point efficiency, the league evolved rapidly. Big men developed perimeter shooting skills, guards spaced the floor differently, and entire offenses were redesigned to maximize expected value per shot. The shift in what was measured and rewarded created a shift in how players trained, played, and were evaluated. What does the evolution in MLB and the NBA best demonstrate about how measurement shapes performance?

A university’s sports performance division redesigns its athlete evaluation system. Staff repeatedly cite the popular phrase “What gets measured gets managed,” assuming it came from Peter Drucker. They focus heavily on easily quantifiable metrics such as sprint times, weight-room numbers, and GPS load data. Over the next season, athletes begin overemphasizing measurable outputs while neglecting unmeasured but crucial areas like mental health, leadership behaviors, and team cohesion. Injuries also rise because players push themselves to meet numerical targets. Which interpretation—based on V.F. Ridgway’s actual meaning of the phrase—best explains what went wrong?

When 0.250 mol of CH4(g) reacts with excess Cl2(g) at constant pressure according to the chemical equation shown below, 177 kJ of heat are released. Calculate the value of ΔH for this reaction, as written.2 CH4(g) + 3 Cl2(g)→ 2 CHCl3(l)+ 3 H2(g)    ΔH = ?