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.
Logan Hughes Case Study Transcript
AXON: What were your main challenges before using Axon?
Logan: Our main one was the time it took in manual labor to be able to regularly, on a weekly basis look at All Whites performances and data and the leagues. Only having one to two analysts here, but now with Axon
it's all auto populated through the program that you guys have built. So it's a seamless process of just refreshing the platform and we get the data straight away. So my time and energy is spent now on analysing the data instead of just having to collect it.
AXON: How has game analytics changed?
Logan: Yeah. Very similar. Like everything in the game analytics before was all self coded. So again, I spent a lot of time and manual labour the coding. Team and individual KPIs.
Whereas now Axon have been able to tailor that through the platform to make it, the KPIs relevant to us. So mirroring our team and individual KPIs, but they're again, self populated from the WyScout data we script and the APIs. So, it saves me so much time as an analyst. And I know that the data is reliable because we've crossed paths with yourself and Ben, and working together means that the data that's populated is how we want it and we can use it in a very quick, within 24 hours on tour after the games to provide extra insight to the coaches and the players.
AXON: How has player tracking changed your work?
Logan: The future goal and what we've started to trickle in now, thanks to the Axon platform, is that it can help selection process.
We can use the data to track players performances. Which areas are they strong in the club? Which areas are they weak in their club performances? And relate that back to the All Whites game model. And then obviously when they come into camp, it starts with really good discussion points for me as an analyst, when I do individual analysis with the players. So I might sit down with one player and we'll work on video and data based off a weak data point that we saw in the Axon player tracking. Or we'll keep mentioning a strength and say, we want you to bring this strength into our games because through the Axon platform it shows that you're really high in this, so can you integrate this into our game model? So it works in two ways. It's most, I would say it's mostly being used, to support and guide individual analysis on tour with the players now to improve their performance on the field.
AXON: Are you using this data with players already?
Logan: Yeah, actually we'll show them or we'll communicate to them. Or it might even be if they're away at their clubs, a simple WhatsApp message, just to maybe a screenshot or even just a message saying, look, you're doing really well in this area. Or, maybe this is an area of weakness just to get your conversation rolling.
And then we'll let the video take it from there.
AXON: How have players responded to the data?
Logan: Every player has a different situation as to how much analysis they've been exposed to in the past, especially individual analysis.
Individual analysis is very, I'll say niche and new in the football world, but become more common practice and from an international team point of view as the lead analyst, it's something that I really value and I think I can offer to the players from an outside perspective.
I think the players, especially the younger generation, really, really gripped onto the data and they know how to integrate it and take it, considerably with their performances. And again, just start some really good tactical conversations for us around their playing style. So I would say especially the younger generation are really attracted to the data that, that's being produced.
AXON: How will you evolve the use of data with players?
Logan: I think next steps are starting to form individual profiles and starting to set goals within. So we'll say, okay, this is what you've been achieving in this metrical data point. Can we start to push into this? So it might be five up to 10, six up to eight. An example might be, we have a winger and we say, look, as part of your playing style, both in your club and All Whites environment, we wanna see your successful dribbles raised from 60% to 75% in the next six weeks.
So we can start setting measurable goals. Through the data that correlate to enhanced performance on the field. And, I think that's where it's gonna go next is setting those personalised KPIs, not just per position, per player. We can set goals based on each individual's playing style that again, directly connects to the All Whites playing style and what Darren Bazeley wants as a coach.
AXON: How was the transition to using Axon?
Logan: Yeah, it's been pretty seamless. Like yourself and Ben have been excellent in, coming going to call it the gritty hard data work behind the scenes. Really for me it's, I have a look now, I tweak, I give suggestions to yourself or Ben, and it's fixed within 24 hours or even less. So super seamless process in terms of integrating Axon, and then things that help with that are generally the visual aspects. Is it attractive for a player and a coach to look at which the Axon platform is? Is it simple to read?
Can we understand it? Is it scalable from one player to another, or team against team comparable? So it's a super user friendly platform.
So as a company, Axon made the process seamless, in terms of my analysis process it's just enhanced add-on for me. Like I've, I typically see myself if I had to put a tag on it as a tactical video analyst. So the data area is an area I've always lacked and I haven't thoroughly stepped into as much, but by using yourself, Ben and Axon, now I'm starting to learn as analyst and I'm starting to learn the power of the data and how I can use the data to start my tactical conversations and use as extra evidence as well.
So from an individual analysis point of view, integrating Axon and the data has enhanced me as well and what I can offer to the players and the coaches.
AXON: How are coaches using the new reports?
Logan: So we'll use the match reports. We'll be integrated into our official post game reports. So the match reports Axon does, we'll integrate that into our All Whites match report or post tour report.
Now, again, more saving me time, manual labor, and the coding. What it allows me to do is deeper dive into the analysis that's already being produced by Axon. And again, it's been tailored to our KPIs in terms of the player club tracking. I'll update the coaches potentially once every three, four weeks, do an overview of our players, where they're scaling and their leagues, and how they're scaling against each other.
So the coaching staff haven't had, and I don't think necessarily need direct access to Axon at the moment. That might be a step forward in the future, but it comes through me and then I pass on the most important information to the coaches to inform them. If any questions come back to me, then I'll show them through the Axon platform and where the integration comes from.
AXON: What is the impact on your time and analysis depth?
Logan: It's taken away hours, literal hours of manual coding and added on those same hours for more deep analysis, more insightful analysis. Why are these data points coming up? Because everything I do is in a time constrained manner. I need to produce reports, but I also need to get ready for the next opponent. So it allows me to focus on the big rocks and the most important thing, which is the data and why it's there.
What is it showing, what's the rationale behind it? How can this data help us? Change for the next game. How can it improve on field performance? What areas are we weak in? So I can ask all these bigger questions, and do proper analysis as opposed to just manual coding. So saves me hours and adds on hours into more insightful research.
AXON: What has been the biggest impact and benefit?
Logan: I think having a template which is visually appealing. Produce in a minimum time scale and frees me up to do deeper research into our playing style are the biggest benefits. So I can very quickly look now after the game, within 12 hours, 24 hours I can analyse our playing style.
I can analyze matches without having to spend 3, 4, 5 hours coding games and then going back and doing the analysis, which is a multitask. So if I was to summarize it, I would say it's a, a time saving tool, or a time efficient tool. It's allows me as an analyst to. Do more deeper diving research and insightful study to spend my time more wisely.
But it also informs me and highlights areas that I might normally miss because Ben and Axon have added in certain statistics and data that I might not have thought of previously, such as the forward to back pass ratio. That's really insightful data for us from an individual point of view. So the scale of data that's being produced so quickly, it's not too large that you get lost in it and it's not too refined that with copy and pasting the same over and over again.
So right now it's a really nice balance where I know I'm getting what I want in terms of our team individual KPIs. But yourself, Axon and Ben have also produced in a way where there's flexibility and variability for new metrics to come in. Which may tell us more story and give us more evidence linked to our playing style.
My last point would be everything we track in there directly comes from the coaches playing model and playing style. So we know it's all being used and we know that every single data point is extremely important to us and will tell a part of the story. It just allows me to spend more time effectively on how we can win our next game and how we can improve individual forms.
AXON: What is your long-term vision with Axon?
Logan: Yeah, access to this. This data in this service, I now see as critical, leading into all of our future games as an All Whites international team. It's an area which myself as an analyst and perhaps the team have lacked in, in the past. So it's an area of opportunity for us to grow. And I know that. If it's used effectively to its fullest capability, can have a really powerful effect on the players and the team.
And it can really help us win football games. So my vision is to continue integrating these programs, and these services, but delve into what's next and how we can get more out of it. Because I understand there's a huge world and much more data that we could use in different ways, to help us grow and be more competitive on the pitch.