Tuesday was the most popular day that new appointments were released.
1PM was the most popular time that new appointments were released.
Over the past 7 days you would have had to check 35 times for a 95% chance of finding an appointment.
Tuesday was the most popular day that new appointments were released.
1PM was the most popular time that new appointments were released.
Over the past 7 days you would have had to check 35 times for a 95% chance of finding an appointment.
We've been keeping track of the appointment availability for San Francisco Global Entry Enrollment Center and hope the data we've collected can help inform your search for a Global Entry appointment.
When is the best time to check for an appointment? Check out these trends over the last 4 weeks!
This plot shows the number of appointments added per week for each day, averaged over the last 4 weeks.
This plot shows the number of appointments added per week for each hour, averaged over the last 4 weeks.
This plot show the same data as the previous two plots, but here you can see which specific hour of each day appointments are being added.
Finding an appointment is hard! We've calculated your odds from our data. We also show how far away the average appointment is.
In this plot we calculate the probability of finding an appointment under 30 (default) days away. This is calculated by summing the total time that an appointment under 30 days is available within a 7 day window. We then divide by 7 days to produce the fraction of time that an appointment is available within 30 days. We compute the rolling average of this probability within a 7 day window and plot at the midpoint date of the window.
The number of checks required to ensure a 95% chance of finding an appointment within 30 days is calculated directly from the probability itself: log(1-0.95) / log(1-p)
In a rolling 7 day time window, we calculate the average number of days away the closest appointment is. This is just the average of each appointment in the table below, weighted by the duration of it's availability. When no appointment is available, we use the maximum of the data set.
We record the nearest available appointment and track when it changes. Here we show a histogram of the number of days away the new appointment is from the time we spot it.
Here we show the faction of time appointments were available based on the number of days away they were from the time we spotted them.
Here are the changes in the nearest appointment over the last 10 days. It shows the date and time at which we found the nearest appointment had changed, the date of the new nearest appointment with the corresponding number of days away, and the time this appointment remained the soonest availble.
We continuously monitor the nearest available appointment date and time. When the status of the nearest appointment changes, we record the new nearest appointment. We additionally record the number of appointments available on the day of the nearest appointment, and make a new record when this number changes.
Added Appointment: When the nearest appointment is earlier than the previous nearest appointment, we consider the new appointment to have been added.
Number of Appointments Added: When a new appointment is added, we count the total number of appointments available on that day and consider this the number of appointments added. In reality, appointments are likely added in subsequent days as well. We don't read that information, however, so our count does not reflect the total number of appointments available. We expect our number to be proportional on average to the actual total, however, so the plots showing the number of appointments relative to other times remain useful.
Probability of Finding an Appointment: We calculate the probability of finding an appointment under 30 (default) days away. This is calculated by summing the total time that an appointment under 30 days is available within a 7 day window. We then divide by 7 days to produce the fraction of time that an appointment is available within 30 days. We compute the rolling average of this probability within a 7 day window and plot at the midpoint date of the window.
Number of Checks Needed: We calculate the number of checks required to ensure a 95% chance of finding an appointment within 30 days directly from the probability itself: log(1-0.95) / log(1-p)