Playtomic Data Export: How to Analyze Bookings in Excel or Google Sheets

Sooner or later every club manager asks the same question: how do I get my Playtomic data into a spreadsheet so I can answer questions the standard reports don't? Which hours are really empty? Which players stopped coming? Is revenue per court-hour going up or down?

This guide walks through a practical Playtomic data export workflow for Excel and Google Sheets: what to export, how to clean it, the pivot tables and formulas that answer the most common venue questions, and the point where manual exports stop being worth the time.

What to export from Playtomic

Playtomic Manager includes reporting and export options; exactly what is available depends on your account setup and permissions. Whatever the menu looks like, aim for a booking-level export—one row per booking—rather than a pre-aggregated summary. Row-level data lets you slice by hour, court, player, and price yourself.

The columns you want, under whatever names your export uses:

Export a full date range you can compare—at least the last 90 days, ideally 12 months for seasonality. Keep the raw export file untouched in its own tab or folder; do all work on a copy.

Step 1: Clean the data before you analyze it

Most spreadsheet mistakes come from skipping this step.

Fix dates and times

Exports often arrive with dates as text, or with date and time in one column. Split them into:

• Date (a true date value, not text).
• Start hour — in both Excel and Google Sheets, =HOUR(B2) returns the hour from a time cell.
• Weekday — =TEXT(A2,"ddd") gives Mon, Tue, and so on.

Check the timezone. If bookings at 19:00 show up as 17:00, the export is in UTC and every hourly chart will be wrong.

Calculate court-hours

Bookings are not all 60 minutes. Add a court-hours column: duration in minutes divided by 60. A 90-minute padel booking counts as 1.5 court-hours. All occupancy math should use court-hours, not booking counts.

Separate cancelled and completed bookings

Add a simple flag column: completed = 1, cancelled = 0. Use it to filter revenue and occupancy, and to calculate cancellation rate separately.

Normalize names

Courts named "Court 1", "Pista 1", and "P1" across different months will split your pivot tables. Standardize with a lookup table.

Step 2: Pivot tables that answer real venue questions

With clean rows, a handful of pivot tables answers most management questions.

Occupancy heatmap by hour and weekday

• Rows: start hour.
• Columns: weekday.
• Values: sum of court-hours (completed bookings only).

Then convert to occupancy:

$$\text{Occupancy} = \frac{\text{booked court-hours}}{\text{courts} \times \text{weeks in range}}$$

for each hour-and-weekday cell. Apply conditional formatting (a color scale) and you have the heatmap that shows your real peak hours and dead zones.

Revenue per court-hour by time band

• Rows: time band (create a column that labels each booking peak, standard, or off-peak).
• Values: sum of price, sum of court-hours.

Add a calculated column: revenue divided by court-hours. If off-peak earns far less per hour than you expected, discounts or packs are eating yield. The revenue per court metric is the one to watch over time.

Utilization by court

• Rows: court.
• Values: sum of court-hours.

Courts that consistently trail others usually have a reason: worse lighting, outdoor exposure, or players' preferences. Use this before deciding on maintenance windows.

Repeat bookings and retention

• Rows: player ID.
• Values: count of bookings, minimum date (first booking), maximum date (last booking).

From this you can count players with 2+ bookings (repeat booking rate) and spot regulars whose last booking was more than 30 days ago—your win-back list.

Step 3: Useful formulas for Excel and Google Sheets

These work in both tools.

Count completed bookings in a weekday hour:

=COUNTIFS(Weekday,"Tue",StartHour,19,Completed,1)

Sum revenue in a date range:

=SUMIFS(Price,Date,">="&F1,Date,"<="&F2,Completed,1)

Average booking value:

=AVERAGEIFS(Price,Completed,1)

Lead time in days (booking start minus booking created):

=A2-H2

Days since a player's last booking:

=TODAY()-MAXIFS(Date,PlayerID,J2)

Name your ranges (Date, Price, PlayerID, and so on) so formulas stay readable when the export grows.

Step 4: Build a simple monthly dashboard

On one summary tab, track the same numbers every month:

• Booked court-hours and occupancy (overall and by time band).
• Revenue and revenue per court-hour.
• Average booking value.
• Cancellation rate.
• New players and repeat booking rate.
• Players at risk (no booking in 30+ days).

Compare each month with the same month last year, not just last month. Seasonality—summer peaks, holiday dips, weather—makes month-over-month comparisons misleading. See year-over-year trends for why longer history matters.

Common spreadsheet mistakes

• Counting bookings instead of court-hours. A day of 90-minute bookings looks "emptier" than it is.
• Including cancelled bookings in revenue. Inflates performance and hides refund problems.
• Mixing timezones. Shifts every hourly chart.
• Overwriting the raw export. You lose the ability to re-check a number.
• One-off analyses nobody repeats. A beautiful pivot table built once doesn't change decisions; a simple sheet updated every week does.

When manual exports stop being worth it

Spreadsheets are great for answering a specific question once. They get painful when you need the same answers every week:

• Every refresh means a new export, re-cleaning, and re-pasting.
• History is limited to whatever exports you remembered to save.
• Multi-venue groups multiply the work by the number of locations.
• Different team members end up with different versions of "the numbers."

If you are rebuilding the same pivot tables every Monday, it is time to automate. CourtPulse syncs your Playtomic bookings on a schedule, keeps your full history, and shows occupancy heatmaps, revenue per court-hour, and player retention without exports—while still letting you export your data whenever you want a spreadsheet.

Frequently asked questions

Can I export my bookings from Playtomic?

Playtomic Manager offers reporting and export options; availability depends on your account and role. If you can't find a booking-level export, ask Playtomic support what your plan includes.

Is Excel or Google Sheets better for Playtomic data?

Both handle the formulas and pivot tables in this guide. Google Sheets is easier to share with a team; Excel handles very large exports and complex models better.

How do I calculate court occupancy from a booking export?

Sum booked court-hours (duration in hours, completed bookings only) and divide by available court-hours: number of courts × opening hours × days. Do it per hour and weekday to find peaks and dead zones. The court occupancy calculator does the arithmetic for you.

How often should I export and review the data?

A short weekly review catches problems early; a deeper monthly review tracks trends. Our 15-minute weekly venue review gives a simple routine.

How can I see Playtomic data without exporting it?

Tools that connect to your Playtomic account—like CourtPulse—sync bookings automatically and present dashboards, so you skip the export-and-clean cycle.

Turn exports into decisions

A Playtomic data export in Excel or Google Sheets can answer almost any question about your club—if you clean it properly, measure in court-hours, and track the same metrics consistently. Start with the heatmap and revenue-per-hour pivots; they reveal the most in the least time.

👉 When the weekly export routine gets old, start your 7-day CourtPulse trial and get the same insights from your Playtomic data automatically.