2025 Flashcard Analytics Report: 301,432 Reviews Across 52,764 Cards

In a concise year‑in‑review, the author presents a quantitative snapshot of his 2025 spaced‑repetition activities, focusing on breadth of exposure, pattern of retention, and systemic behaviour of a custom-built flashcard platform. ## Review Volume and Card Base Staged across the calendar, the system recorded **301,432 review events**. These encompassed **52,764 unique cards**, a figure that reflects approximately five reviews per card on average. The review cadence never included an interval longer than **13 hours and 55 minutes**; the system’s design—mixing random and scheduled cards—ensured continuous engagement and mitigated potential lapse windows. ## Sustained Daily Practice Since **March 25 2023**, the author has maintained an unbroken daily review streak. This steady cadence signals a strong commitment to long‑term retention and aligns with best practice recommendations for spaced‑repetition frameworks. ## Accuracy Metrics **Overall accuracy**—measured by random card sampling—stands at roughly **89 %**. That suggests that about 49,000 of the 55,000‑card library are answered correctly on average at any given moment. Accuracy on due cards often appears marginally higher; however, this artifact primarily derives from the fact that recently created and missed cards, which are inherently easier, populate the due queue. When conditioning on a longer preceding gap, random reviews are indeed more difficult than schedule‑driven ones. ## Notable Card Performance The card with the highest miss count in 2025 (“Merrily We Roll Along” trivia about Michael Curtis and the 1934 *Porgy* authors) was missed **39 times**. This outlier prompts further investigation into potential content complexity or card design weaknesses. ## Time‑of‑Day Effects Initial analysis indicated stronger performance during morning hours (90‑91 %) and a surprise spike (~91 %) in the 5‑p.m. window, likely tied to a brief post‑shower study session. Yet, statistical tools from advanced language models (ChatGPT, Gemini) deemed these differences **not statistically significant** despite sizeable sample counts. The author expresses interest in a deeper statistical exploration of diurnal learning effects and invites collaboration from experts in memory training. ## Conclusion The 2025 data set illustrates a disciplined implementation of spaced repetition, with robust engagement metrics and an overall high accuracy rate. Future work will focus on refining scheduling algorithms to balance ease and challenge and on validating time‑of‑day performance insights with rigorous statistical analysis. --- *Author: Nate Meyvis – ongoing contributions to the blog‑based flashcard community.*