Logan Hughes Goes From Manual Coding to Timely Insight.

Within an international men’s football programme, performance analysis operates under unique constraints, including limited contact time with players, a globally distributed player pool, and short preparation windows around international fixtures.

As part of a pilot collaboration, the New Zealand men’s international football performance team has been working with Axon Perform to explore how automated data pipelines and bespoke dashboards might support existing analysis workflows. The focus of this exploratory phase has been on improving efficiency and consistency while aligning outputs with the programme’s established KPI framework.

The Challenge: Monitoring a Global Player Pool Efficiently

Historically, monitoring player form across multiple clubs and leagues required significant manual effort. Analysts spent large portions of their time collecting data, coding matches, and aligning multiple sources before interpretation could begin.

This created pressure on limited analyst resources, particularly during international windows where time for deeper analysis was restricted. As described during the pilot, much of the workload previously centred on preparation rather than insight.

The Approach: Automated Data Aligned to Existing Frameworks

Through the collaboration with Axon Perform, automated data feeds and dashboards were configured to reflect the programme’s existing KPI structure at both team and individual levels. Data sources were integrated via scripted pipelines, with outputs shaped collaboratively to ensure relevance and accuracy.

A key principle of the pilot was alignment with existing language and performance models, rather than introducing unfamiliar reporting structures. As noted during the process, the value came from having data that was already framed in a way coaches could engage with.

Match Analysis and Reporting

Post‑match analysis was one of the first areas explored. Automated match outputs reduced the amount of manual coding required, enabling analysts to move more quickly into interpretation and contextual review.

Reflecting on this shift, the analyst involved noted that automation has "saved a significant amount of manual work, allowing the focus to move more quickly toward analysis and discussion with coaches during tours and international windows".

Logan Hughes

Player Monitoring and Development Conversations

The pilot also supported improved visibility of player performances across club environments. Unified dashboards allowed analysts to review trends, strengths, and areas for development across the wider player pool, helping connect club output with national‑team expectations.

These insights were used to support development conversations with players, both during camps and remotely. As described in the pilot, "we might sit down with a player, use video and data to look at a specific area, or highlight a strength we want them to bring into our game model".

Individualised KPIs and Goal Setting

An area currently being explored is the use of individualised KPIs, informed by positional demands and individual player profiles. This approach supports the setting of short‑term, measurable goals that can be tracked consistently over defined periods.

During the pilot, this was described as enabling analysts to "start setting measurable goals through the data, linked back to the playing style and behaviours we are looking to reinforce".

Impact on Analyst Workflow

The most significant impact of the pilot has been a rebalancing of analyst time. Automation has reduced hours spent on repetitive data tasks, creating greater capacity for higher‑value activities such as trend analysis, opposition preparation, and supporting coaching discussions.

As summarised during the trial, the tools have "taken away hours of manual coding and created more space to focus on deeper analysis and the bigger performance questions".

Reflections from the Pilot Phase

From the perspective of the analysis team, the collaboration has demonstrated how well‑aligned data infrastructure can support international football environments with limited preparation time.

The pilot continues to inform how data, video, and insight can be integrated more effectively into performance workflows, particularly in the lead‑up to major tournaments and international windows. This case study reflects a defined exploratory phase and is descriptive in nature.