You can be calibrated at 50% and still be less accurate.
A constant 50% forecast is calibrated when half the outcomes happen. It cannot distinguish a likely case from an unlikely one, which is where better forecasts gain accuracy.
Run a calibration check
Use one probability bucket and its observed outcomes. The calculation runs entirely in this browser.
Sample loaded: a perfectly calibrated 50% bucket.
Measured result
Calibration is closeness of the forecast to the observed frequency. Accuracy here is the share correct when each forecast is turned into its most likely binary answer.
95% observed-rate interval: 36.6% to 63.4%.
Calibration is one axis.
Discrimination is another.
When every case gets 50%, the forecast makes the same decision every time. It can be calibrated across many cases, yet it leaves no room to rank cases. A more accurate forecaster can remain calibrated while using 70% for cases that happen often and 30% for cases that do not.