Cutting And Editing – Catapult Support

This guide covers the basic steps for collecting accurate sports performance data, helping you effectively assess player load and optimise your training sessions.

Uploading Data

After the session, connect Vector 8 Devices to Vector 8 Dock to upload device data to Cloud.

Travelling or working behind a captive portal? If your venue uses a captive portal (e.g. hotel or stadium WiFi) or you are experiencing dock connectivity issues, the standard upload may not be possible. Use the Vector Desktop app to transfer data via USB from the Dock to your Windows PC instead. See the Vector Desktop App article for full setup and usage instructions.

Graphing Data

Before editing a session, you must first check the quality of the recorded data. The easiest way to do this is to graph the data, which you can do in the web editor. This process will help you quickly identify the start and end times of drills, and recognise periods of player inactivity (see the Rotation content below).

Understanding Data Segmentation & Creating Periods

It is important to understand that OpenField only processes data from players assigned to a period, so the level of detail in your analysis directly depends on how you segment your data.

A single, unsegmented period - like the default "Autocreated Period" or "LSG - Whole" in figure 1 - often fails to capture the true intensity of specific drills.

Dividing a session into specific, segmented periods (e.g. "LSG A" and "LSG B") along with rest breaks, allows for a more detailed understanding of each drill's true intensity. For instance, while overall volume might remain constant (with small variations in walking distance), the intensity metrics, like meters per minute, can increase significantly from 100 m/min in “LSG - Whole” to 137 m/min in “LSG - A” and 145 m/min in “LSG - B”, which is a considerable difference.

Figure 1: Segmented periods (LSG - Part A and Part B) allowing for separate analysis

Adjusting for Player Rotation & Benching

For team drills and games with rotations, like a 4v4v4 setup or when players are substituted in a game, it's crucial to account for player rest periods. Players on the sideline naturally accumulate less volume and show lower intensity metrics than those who are active.

Factoring in these variations ensures fair and balanced workload distribution across the team. This also allows you to accurately assess the performance of each player, taking into account their rest periods.

This can be done via the Benching/Rotating, which excludes all the data of that player in the selected region and reduces a player's total duration by the benched time (Figure 2).

Figure 2: Benching inactive time for Player 1 in Drill 3 to get the true duration and intensity

Adding Context through Match Benchmarking & Tactical Analysis

One of the most valuable aspects of segmenting data is its role in benchmarking. For example, comparing the intensity of a 5-minute match segment to the intensity of training drills helps ensure players are adequately prepared for the demands of actual game situations.

Using Annotations for Benchmarking

Analysis can be conducted in parallel with period data by using annotations. By generating time-based annotations, you can create custom time segments within a period and analyze physical outputs.

For example:

Create a “First Half” period for a match
Add 5-minute annotations within that half
Import them into the activity

This allows you to observe the flow of a half, identify the most strenuous periods, and pinpoint when multiple high-intensity intervals occurred. These annotations can be visualised in OpenField Cloud, making it easier to showcase and share insights. We will walk you through the interpretation and reporting options in Step 7 and Step 8 of the onboarding.

Combining Tactical Analysis & Eventing Data

Annotations can also be used to import eventing data and tactical information from video-analysis tools such as Focus. By combining physical data with tactical context, you gain a more comprehensive view of athlete's performance.

Examples include:

Comparing physical metrics in possession vs out of possession phases
Measuring intensity in high-press situations
Assessing individual work rate during counterattacks

For more details see: Integrating Focus and OpenField Data.

Applying Tags

Using the tagging template introduced earlier, tags should be applied as the final step of the editing process. While tags can be added in several places, we recommend doing so in the Tagging menu in OpenField Cloud, as it offers the full range of options.

Additional Note

Some cutting and editing tasks can also be performed live, which offers additional benefits (see Step 5: Live Usage Of The System of the onboarding).