Which statement about data quality in sports analytics is accurate?

Which statement about data quality in sports analytics is accurate?

• A. Objective, valid, and reliable data about performance
• B. Data is best when collected from a single event
• C. Subjective impressions are sufficient for decisions
• D. Data quality is not important for analysis

Answer: (A)

In sports analytics, data quality means using measurements that are objective, valid, and reliable. Objective data come from observable facts rather than personal opinions, ensuring decisions aren’t swayed by bias. Valid data truly capture what you intend to measure—so the metric reflects the performance or outcome of interest. Reliable data are consistent across repetitions, observers, and time, so results don’t jump around with minor changes. When data meet these properties, analytics can accurately compare performances, track improvement, and build trustworthy models. Relying on a single event can distort conclusions due to unique circumstances, and subjective impressions don’t provide the measurable evidence needed for sound decisions, while ignoring data quality undermines any analysis.

In sports analytics, data quality means using measurements that are objective, valid, and reliable. Objective data come from observable facts rather than personal opinions, ensuring decisions aren’t swayed by bias. Valid data truly capture what you intend to measure—so the metric reflects the performance or outcome of interest. Reliable data are consistent across repetitions, observers, and time, so results don’t jump around with minor changes. When data meet these properties, analytics can accurately compare performances, track improvement, and build trustworthy models. Relying on a single event can distort conclusions due to unique circumstances, and subjective impressions don’t provide the measurable evidence needed for sound decisions, while ignoring data quality undermines any analysis.