The Flo application is a widely used cycle tracking tool that helps individuals monitor and understand their reproductive health. When the app displays the message “Period may start today,” it signifies that this date is the most statistically probable onset of menstruation for the user. This prediction is not a guarantee but rather an informed estimate based on a continuous analysis of past data. Understanding this message requires looking closely at the sophisticated data processing and recognizing the natural variability inherent in the human menstrual cycle.
The Data Behind Flo’s Prediction
The prediction that a period “may start today” results from a complex calculation utilizing two main categories of information. The first is the detailed data a user manually inputs, including past cycle lengths, previous period dates, and logged symptoms like pain, mood, and discharge intensity. This historical record provides the foundation for identifying a user’s unique menstrual patterns. Additional data, such as age, height, weight, and information from synced wearable devices like activity or sleep statistics, are also factored into the analysis.
This user-supplied information is processed by advanced algorithmic systems, specifically machine learning models and neural networks. These algorithms analyze the large volume of individual data points to identify subtle, stable patterns that repeat across cycles, rather than just calculating a basic average. The neural network learns the specific relationship between a user’s logged symptoms and their cycle timing, improving prediction accuracy over time. By continuously comparing its predictions to the actual logged start dates, the algorithm fine-tunes its model, delivering a statistically probable number of days until the next cycle begins.
Understanding Cycle Variability and Prediction Accuracy
The prediction that a period “may start today” represents the day with the highest probability, but the menstrual experience is rarely exact. Since the timing of ovulation can shift, the overall cycle length often exhibits natural variation. This biological reality is why the app frequently provides a prediction window of several days rather than a single fixed date, acknowledging that menstruation can reasonably begin within that range.
The length of a menstrual cycle, typically ranging from 21 to 35 days, is susceptible to change from numerous internal and external influences. Biological factors, such as minor hormonal fluctuations or shifts in the ovulation day, directly affect the timing of the next period. External factors can also delay the cycle by altering the body’s expected rhythm, causing the statistically probable date to shift.
External Influences
External factors that can alter the body’s expected rhythm include:
- Sudden increases in physical activity.
- Significant changes in diet.
- Travel that causes jet lag.
- Periods of intense emotional or physical stress.
The prediction model in the Flo app is dynamic, meaning it updates the forecast as new information is logged. Even with advanced machine learning, the inherent variability means that the predicted date should be viewed as the center of a probability curve, not a fixed deadline. The app’s accuracy improves with more consistent data logging, but it cannot perfectly account for all sudden, unpredictable life events that influence hormonal signals.
When the Predicted Start Date Passes
If the “period may start today” notification passes and menstruation has not yet begun, a short delay is a common occurrence. The user should continue logging any symptoms and note the delay within the application, as the algorithm will adjust future predictions based on this new cycle length. Since the period is considered late if it exceeds the predicted start date, a negative pregnancy test can rule out the most common reason for a delay.
Delays often occur because ovulation took place later than usual, which naturally extends the overall cycle length. The app may automatically shift the prediction to the next day, helping maintain the accuracy of the cycle count. Users should consider seeking medical advice if the delay is prolonged, such as if the cycle has exceeded 35 days or if a normally regular cycle is more than three days late. Consulting a healthcare professional is also advisable if the delay is accompanied by severe or unusual symptoms.