Mistakes & Mixed Signals

Limitations of fertility tracking methods

Limitations of fertility tracking methods

Why fertility tracking has real limits Fertility tracking is built around probability, not certainty. Most methods try to estimate the fertile window, the short span in which pregnancy is possible, by observing past cycle patterns or current biological signs. That can be useful, but it is not the same as directly observing ovulation in real […]

How to interpret conflicting tracking signals and troubleshoot issues

How to interpret conflicting tracking signals and troubleshoot issues

What a tracking signal is and why discordance matters A tracking signal is a simple bias metric. In forecasting terms, it compares cumulative forecast error with mean absolute deviation, which is a way to ask whether errors are canceling out or consistently leaning in one direction. If the number stays near zero, the forecast is […]

Limitations of fertility tracking and when it is not effective

Limitations of fertility tracking and when it is not effective

Why fertility tracking has built-in limits Fertility tracking is based on observing menstrual-cycle signals such as bleeding patterns, cervical mucus, and basal body temperature. Some approaches also use luteinizing hormone tests or app-based algorithms. The idea is reasonable: if ovulation can be estimated, then the fertile window can be narrowed. The limitation is that the […]

Common mistakes in fertility tracking

Common mistakes in fertility tracking

Why fertility tracking is easier to misread than it looks Fertility tracking sounds straightforward: observe the menstrual cycle, identify ovulation, and use that information to guide intercourse or contraception. In practice, the biology is more variable. Ovulation does not always occur on the same day from cycle to cycle, and the visible signs of fertility […]