May 13, 2025 • 18 mins
In the latest episode of the Lifting the Lid on Technology, host Barry sits down with Adam Foy, Head of Performance Analysis at the Blues Rugby team, to explore the high-performance world where data, coaching, and game-day decisions intersect.
From Adam’s roots at Munster Rugby and the Irish National team to his current role in at The Blues in New Zealand, discover how advanced tools like Hudl SportsCode and Power BI help shape training, analyse the opposition, and tell a compelling data story.
Whether you're a sports fan, data enthusiast, or IT professional, this episode reveals the powerful role of tech in high-performance environments.
See omnystudio.com/listener for privacy information.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
S1 (00:05):
Welcome to another episode of Lifting the Lid on Technology,
your go to source for insights into the latest tech
and innovation. My name is Barry White, your host and
CIO at Soft Source Bridge. This episode is brought to
you by our partner, HP Advancing workplace Performance with AI
driven devices. My guest today is Adam Foy, head performance
(00:30):
Analysis from the Blues. Great to have you here today, Adam.
S2 (00:34):
Thanks, Barry. Happy to be here.
S1 (00:36):
You must have probably one of the best jobs in
the country. Get to watch rugby every day and get
paid for it. You must be the envy of all
your friends.
S2 (00:44):
Yeah, no it is. It's definitely a bit of a
niche role. But then, yeah, there's a lot of kind
of falling into it. And yeah, I've loved it the
last couple of years.
S1 (00:51):
You've been with the blues now. This must be your
third season. Have I got that right?
S2 (00:55):
Third season. Yep. Yep. Came early 2023. Um, yeah. Third
good season in there.
S3 (00:59):
Do you want to tell us a little.
S1 (01:00):
Bit more about your role? You know exactly what a
performance analysis does. And, uh, maybe also, you know, given
your background from Ireland, a bit of history about your
time with Munster and the national Irish rugby team as well.
S2 (01:14):
Yeah. So, yeah, I lead the analysis of the Blues
and lead a team of for Josh Johnson's our assistant
analyst and we have Brad Sherwood and dumb all those
who've come through and they do a great job for
us as well. Um, and then obviously Julie Harris is
our women's team who and had a great win at
the weekend. And she looks over some of the IT
stuff as well. So yeah, it's a bit of a
(01:36):
pretty big team. But I suppose for me my role
probably quite embedded in the coaching process. So I'll be
sitting in with the coaches every day in on meetings, etc..
And I suppose the crux of it is you're trying to, um,
provide information, um, that creates insight to help performance at
the weekend and improve players and ultimately get a few wins. Um,
(01:56):
it's the nuts and bolts of it.
S1 (01:58):
Your background in Ireland, how you got started in Munster?
From what I understand, that was your first real role
where you were doing this type of work?
S2 (02:07):
Yes. I was pretty fortunate that I got an internship
straight out of uni with the Munster senior team and
did two years there, um, which was a great learning experience,
some great mentors there and gained a lot from the
coaches and players fortunate enough to get into the Irish setup.
S1 (02:23):
Yeah.
S2 (02:23):
Pretty, um, early on in my career. Same again. It
was a brilliant education for me. And in terms of
what high performance sport looked like, and dealing with some
of the top coaches and players in the world. And
from there, I was always quite a small network and
you get to know people and meet people. So couple
years after that and a few connections from there, Kiwi
(02:46):
connections that were there at the time told me that
there was potentially an opportunity to blues. So yeah, a
couple interviews out there and maybe two months later I
was in Auckland.
S1 (02:55):
Yeah, well, uh, it's great to have you here. And and, uh,
certainly after last season. That was. That was great. I
guess we won't talk about the season so much, but, uh.
But there's still time, right? There's still time? Definitely.
S2 (03:07):
Yeah, definitely.
S1 (03:09):
So from what I understand, uh, you've also had a
bit of background in coaching as well. And, uh, the
reason I asked that question, um, was more around, I
guess being a data analyst, having that coaching background and
applying background. That must really, really help a lot in
what you're doing. It's not just about crunching numbers, right?
S2 (03:25):
Yeah, definitely. And there's probably a little bit of a
misconception sometimes about what we do or where we sit.
I suppose if you have a spectrum of data and analytics,
one side or and then coaching could feel the other side,
we probably sit in the middle somewhere. Yeah. So again,
data informs to us at times where kind of where
the team can go or areas we can improve on.
But then I suppose the other side of that is
(03:46):
having a deep understanding of the game and background of
the game, and easy to understand with the amount of data,
what's important to look at and where you need to
look at, and to try and bring inside to the
team and help them improve.
S3 (03:59):
So can you paint.
S1 (04:00):
A picture for us? Maybe we'll see. Obviously we see
the coaches booth on TV and we see the laptops there,
and everybody seems to be looking at the laptops while
the game is progressing. Can you kind of paint a
bit of a picture for us? Just how data, I guess,
shapes your planning for each game and training sessions, and
particularly as you're going through the season? You know, imagine
you're not just looking at it from a player performance
(04:22):
point of view, but you're also looking at from the
opposition point of view as well, right?
S2 (04:27):
Yeah, definitely. There's probably a couple of key areas that
we'll look at. So throughout our week, opposition analysis is
obviously massively important. We'll generally work a week ahead of
the team. So it's like today on our day off
I'll be looking at the Reds who we play in
about ten days time, and then we'll have a meeting
with the coaching group on Friday and present, I suppose
the bones of the strategy there, and there'd be some
(04:49):
good robust discussion around how we go with the game plan.
And then from I suppose, the player point of view,
we'll then present that strategy Monday Tuesday to then have
a lot to do with that process. And then obviously
we'll review our own game, review our own players after
games training. Are we training the the plan that we're
trying to execute at the weekend? And then obviously from
(05:11):
an individual point of view is there are certain areas
we can help players with and definitely try to use
data as a tool rather than as a weapon. I
suppose in the past, or maybe at the start when
data analysis was used, might have been more just looking
at the negatives. But can you look at the positives,
can you see improvement and then try and help players
improve in that way as well?
S3 (05:30):
Yeah.
S1 (05:31):
So I guess if we sort of dig into that
a little bit further and I guess for, for our
listeners who are, who are probably not familiar with what
that actually looks like a big part of your role.
So I understand it is obviously looking at, um, you know,
video material and we'll talk a bit about that. And
that's pretty, pretty easy to get your head around. But
but how does that kind of mash up with the
(05:51):
actual data side of it? And I've heard this term
coding used as well. But how do those two things
kind of sit together? And I guess where does that
data come from?
S2 (06:00):
The main software that we use is called Huddle Sports Code,
which integrates video and data and which we what we
use every day and go to the usage on the players,
the ability to use it as well. And so coding
is effectively the tagging clips of the game. And then
layering on data labels to that, that are kind of
(06:23):
key metrics that we would look at. Or we feel
important as a coaching group to monitor. And so that's
part of our data. And then we have third party
data as well from Stats Perform who provide data to
all the teams in New Zealand. And we'll have that
data not just from our game or our competition, but
we can get data on competitions and players and throughout
the world.
S3 (06:43):
Yeah, and correct.
S1 (06:45):
Me if I'm wrong on this, but my understanding is
that the players themselves have a sort of a tracking
device in their shirts as well, and that forms part
of the data. What? I was aware of that from
previous years, but when I first heard about it, I thought, really?
S2 (06:58):
Yeah. So what kind of data tracking? All kind of
the physical metrics. That's more the physical performance side. So
that'll be Mark Bennett and his team and we'll generate
more out of it quite closely. There'll be a bit
of crossover between ourselves and them in terms of how
we we might integrate that into reviews etc. but for
the most part, we're just looking at game data, player
(07:19):
data more based around the actual game than the athletic
performance out of it.
S3 (07:24):
What about.
S1 (07:25):
Referee data? Are we are we all scream and yell
at the TV set? And I think last year's World Cup,
there was a fair amount a fair amount of that
going on, uh, especially with the TMO and so forth.
Does that form part of your part of the data
set that you're looking at?
S2 (07:39):
Yeah, definitely. Yeah, we've started to perform and just as
a player and director of player involvement and code referee
involvement as well. And we'll get all that data through
power BI. We'll definitely look at it each week, depending
on which referee we have and potentially just some of
the variances in types of penalties, they reward that kind
of thing if they're hot on offside or potentially causing
(08:02):
the scrum that we might need to talk to players about.
It's definitely a small part of it, but it can
be an important part, especially as you get into the
business end of the season.
S1 (08:10):
Yeah. What about the TMR? I don't suppose you can
get any stats off there, can you?
S2 (08:14):
No.
S1 (08:17):
I think you should if you want my personal opinion,
but we won't delve into that. Some years ago, I
had the pleasure of spending a very similar, um, podcast
with Troy Webber. Back in those days, he was talking about,
you know, some of the tools he was using and
also some of the challenges he was having around collecting
data and storing data. How has that evolved in your
time there? And I guess where's that heading as well
(08:37):
from a data management point of view? I mean, this
is an IT podcast after all. So I have to
ask a few questions.
S2 (08:44):
Yeah. No, absolutely. Um, yeah. It probably hasn't changed a
massive amount from where it was. Like the answers were great.
They did some great work in providing us with AWS
and all the other teams with quantity and quality of data.
And I suppose it's up to us how we how
we best use it. So that'll come into our power
BI reports too. I think it's Amazon Redshift. And then
(09:05):
we'll layer kind of layer our data on top of that.
So the data that we code and we'll go through
OneDrive and we'll link that into power BI. And then
kind of I suppose that's the bit of the dog
work through the off season, is to create reports that
then can just automate, um, each week once we're in
(09:27):
season or post training sessions as well. So there's not
a whole lot of added visualization of work because, yeah,
as you can imagine, during the season it can be
a bit time poor. So as much as that, we
can automate and be able to see and create insight
and give us focus points each week. It definitely helps.
S1 (09:45):
So how's that evolving with the coaches now? I mean,
one of the things I'm gleaning from this conversation is
that you're very much part of the coaching team, right? Yeah.
And in terms of your role, if I'm wrong on this,
you're on your second coaching team since you've been at
the Blues. Is that right?
S2 (10:02):
Yep, yep. And I suppose, you know, I first came
in with when Leon was head coach. And a lot
of the assistants have stayed the same since I was there.
And then obviously Vern and Jason Halloran and Greg Feek
came in, came in last year. So. And but yeah,
I suppose the evolvement there we go. And head coaches
are different around certain areas of what they want to
(10:24):
look at. So I suppose you're effectively trying to be
a second set of eyes for them. So having quite
a close connection with them, understanding what they want to
see is really important in terms of how we play
and our game model. So basically creating metrics that will
inform them to make decisions is is what's important. So
yeah that does change coaching group to coaching group and
(10:45):
being able to have a good honest conversations and trusting relationships.
Massively important.
S1 (10:50):
When I was going with that question, Adam, and I
guess putting experience back to your time in Ireland as well,
have you noticed between the different coaching styles, has data
played a different role in terms of those relationships? And
I guess is this concept of old school coaches versus
perhaps more modern coaching styles. What have you seen? Some
without naming names of course. Have you seen variances there?
(11:11):
And is that is that maturing?
S2 (11:13):
Yeah I think it's probably slow variances coaching coaching group.
But I think everyone now definitely sees value in it.
And for me it's again it's probably how you present
information to different people. It's not it's understanding that they
might just want to see spreadsheets or data in that form.
But can you show to them maybe understanding what the
data is telling you, but then show video clips, etc.
(11:34):
or some coaches will want want spreadsheets, they want graphs.
So it's probably just understanding preferences really, and how you
get your point across and how you can can add
value is the main thing.
S1 (11:44):
Yeah. So I find it interesting because you really, you know,
if I relate that to the way people use a
tool like power BI in the corporate space, you're telling
a story really, aren't you? You're trying to tell a story.
S2 (11:55):
Yeah, absolutely.
S1 (11:55):
And sometimes that could be relating to the opposition, or
it could be relating to an individual player or whatever
the case may be. And, you know, we talk a
lot about this business, about actionable data, right. And I
think probably more than most applications I come across in
this role, you're probably more actionable than most from the
point of view of you're looking at data and you're
making some pretty probably week on week decisions right around, well,
(12:18):
hopefully impactful decisions that hopefully will influence the outcome of
the game. Right?
S2 (12:23):
Yeah. So we'll definitely use tools like power BI to
to help us storytell and present that to to the
coaches and the players and on a week to week basis.
But also our GM of rugby in terms of recruitment, etc.
we'll have certain dashboards and metrics. We look at different
players and kind of key criteria of players in a
(12:44):
certain position of what we want to recruit, how do
we use data to to inform that. And until we
get through that process as well.
S1 (12:51):
Yeah. Yeah, yeah. So on that question of impactfulness, have
you been have there been situations or incidents that have
occurred over the last few seasons where, you know, without
without naming specific games, you're sort of quietly in the
back of your mind, patted yourself on the back and thought, yeah,
I nailed that.
S2 (13:10):
I suppose it's definitely a collaborative approach. And like the
team that I work with do a great job with
informing certain areas of the game and with the coaches
as well. So it's definitely I just want, you know,
come up with a game plan by yourself. It's very
much a collaborative approach across the whole team. So yeah,
there's certain times of the box when you've seen something
in terms of potentially space or a strategy that we use,
(13:32):
and it comes off that you can tend to get
a bit of a buzz out of it. But, um,
it's about the team doing well at the weekend. So
week to week, it's the main focus is that.
S1 (13:42):
You know, everybody's everybody's talking about AI these days. And um,
you know, you can't get through a technology podcast these
days without talking about AI. What are some of the
technologies out there that you're aware of that may impact
the sport, and particularly in terms of your role as
a as a data analysis? What are there things out
there that you see evolving that that could be really
(14:04):
impactful in terms of the data?
S2 (14:06):
Yeah, I suppose when you look at rugby, it's quite
new in terms of professionalism compared to other sports. And
obviously money is a big thing. But when you look at, say,
the NBA or English football, they have a lot of
tracking data. So tracking players every second, tracking the ball
every second and they range and range of data. So
and and there's there's been some brilliant work and research
(14:29):
going into that and how that's affected those games. So
yeah we are potentially tracking data and the availability of
that could be very interesting to us. I suppose kind
of machine learning and we do do a little bit.
We'll incorporate our into our power BI reports, some regression
analysis around understanding what the key metrics are to winning
(14:50):
certain games, etc.. So that's that's already a part of
our process. But as far as improving that and kind
of train those algorithms, even even more precise, because they
need that keep needing good data in the next level
of data is is the main thing.
S1 (15:07):
So my understanding is that from a data perspective, and
you touched on some of those sources a little bit
earlier on, my understanding is that here in New Zealand
that that is actually centralized around the New Zealand Rugby union. Right.
That's that's is that unique sort of internationally is that.
S2 (15:22):
And I think it depends on, on the unions probably.
I think Ireland and New Zealand are quite similar in
that regard with the franchises or teams being wounded. That's
kind of how our fear ends at AR. I think
potentially in France and England, when the teams are owned privately,
that's probably quite different. And I've seen teams have to
actually go out and have these relationships and build their
(15:44):
own systems. At the end of the day, there's an
awesome job at providing us with all the information we need.
And Jimmy Hamilton, the All Blacks analyst, is really helpful
in that regard too.
S1 (15:53):
And the other thing I was interested in was the
some of the video material we've talked quite a bit about,
you know, data and collecting data, but obviously video is
a major part of that as well. Talk us through
that a little bit, because you get to see video
footage that us mere mortals don't get to see on
Sky TV, right? So we get we get a very
controlled package of material, and it obviously cuts from cut
to cut. But my understanding is that you get to
(16:16):
see all of it, right, irrespective of whether the camera's
live or not. Right?
S2 (16:19):
Yeah, exactly. So we've got, um, four feeds from Sky
into our box. So it'll be that TV view that
everyone will see, and then we'll get a wide view.
Constant wide view, a constant view constantly behind the goal
and and then a tighter view and for more detail
around the rock and set piece. And then added to
that he jumped in. Well, we'll um video a reverse
(16:41):
angle and then a kind of wider view behind the
goal as well. So there's a really good relationship between
all the analysts across Super Rugby specifically. And we'll share
that footage with each other. And yeah, I suppose you
can get access to those for every game. Yeah. And
across the competition. So everyone has access to it. So
that's how you use it best. And the coaches put
(17:03):
a huge amount of time and effort into watching the
video as well. So it's a collaborative process still.
S1 (17:08):
Yeah. So have you ever had any situations where you
thought the TMO was wrong?
S2 (17:14):
Uh, potentially once or twice. Would I not generally be
there doing the best for the game?
S1 (17:19):
Yep. Hey, Adam. Well, there's probably a good place to
kind of stop and, um, look, uh, look, I found
that absolutely fascinating. And I'm really interested to see where
over the next year or two, where it all goes.
And it'll be interesting to come back to that. I
question again in a few years time and to revisit,
to see how that's how that's really impacted the types
of things you're doing with how many games you've got
(17:41):
to go this season.
S2 (17:42):
We have six games left plus a bye week. Yeah,
it's going to cost you just again.
S1 (17:47):
No pressure to add on for that reason. For that
reason I better let you get back to your data.
S2 (17:54):
Thanks a lot.
S1 (17:55):
All right. Great to talk to you.
S2 (17:57):
Cheers.
S1 (18:02):
Thanks for listening to another episode of Lifting the Lid
on Technology, brought to you by our partner, HP. I'm
Barry White, signing off. Until next time. Join us again
for more insights and commentary on the technologies shaping our future.
Welcome to another episode of Lifting the Lid on Technology,
your go to source for insights into the latest tech
and innovation. My name is Barry White, your host and
CIO at Soft Source Bridge. This episode is brought to
you by our partner, HP Advancing workplace Performance with AI
driven devices. My guest today is Adam Foy, head performance
(00:30):
Analysis from the Blues. Great to have you here today, Adam.
S2 (00:34):
Thanks, Barry. Happy to be here.
S1 (00:36):
You must have probably one of the best jobs in
the country. Get to watch rugby every day and get
paid for it. You must be the envy of all
your friends.
S2 (00:44):
Yeah, no it is. It's definitely a bit of a
niche role. But then, yeah, there's a lot of kind
of falling into it. And yeah, I've loved it the
last couple of years.
S1 (00:51):
You've been with the blues now. This must be your
third season. Have I got that right?
S2 (00:55):
Third season. Yep. Yep. Came early 2023. Um, yeah. Third
good season in there.
S3 (00:59):
Do you want to tell us a little.
S1 (01:00):
Bit more about your role? You know exactly what a
performance analysis does. And, uh, maybe also, you know, given
your background from Ireland, a bit of history about your
time with Munster and the national Irish rugby team as well.
S2 (01:14):
Yeah. So, yeah, I lead the analysis of the Blues
and lead a team of for Josh Johnson's our assistant
analyst and we have Brad Sherwood and dumb all those
who've come through and they do a great job for
us as well. Um, and then obviously Julie Harris is
our women's team who and had a great win at
the weekend. And she looks over some of the IT
stuff as well. So yeah, it's a bit of a
(01:36):
pretty big team. But I suppose for me my role
probably quite embedded in the coaching process. So I'll be
sitting in with the coaches every day in on meetings, etc..
And I suppose the crux of it is you're trying to, um,
provide information, um, that creates insight to help performance at
the weekend and improve players and ultimately get a few wins. Um,
(01:56):
it's the nuts and bolts of it.
S1 (01:58):
Your background in Ireland, how you got started in Munster?
From what I understand, that was your first real role
where you were doing this type of work?
S2 (02:07):
Yes. I was pretty fortunate that I got an internship
straight out of uni with the Munster senior team and
did two years there, um, which was a great learning experience,
some great mentors there and gained a lot from the
coaches and players fortunate enough to get into the Irish setup.
S1 (02:23):
Yeah.
S2 (02:23):
Pretty, um, early on in my career. Same again. It
was a brilliant education for me. And in terms of
what high performance sport looked like, and dealing with some
of the top coaches and players in the world. And
from there, I was always quite a small network and
you get to know people and meet people. So couple
years after that and a few connections from there, Kiwi
(02:46):
connections that were there at the time told me that
there was potentially an opportunity to blues. So yeah, a
couple interviews out there and maybe two months later I
was in Auckland.
S1 (02:55):
Yeah, well, uh, it's great to have you here. And and, uh,
certainly after last season. That was. That was great. I
guess we won't talk about the season so much, but, uh.
But there's still time, right? There's still time? Definitely.
S2 (03:07):
Yeah, definitely.
S1 (03:09):
So from what I understand, uh, you've also had a
bit of background in coaching as well. And, uh, the
reason I asked that question, um, was more around, I
guess being a data analyst, having that coaching background and
applying background. That must really, really help a lot in
what you're doing. It's not just about crunching numbers, right?
S2 (03:25):
Yeah, definitely. And there's probably a little bit of a
misconception sometimes about what we do or where we sit.
I suppose if you have a spectrum of data and analytics,
one side or and then coaching could feel the other side,
we probably sit in the middle somewhere. Yeah. So again,
data informs to us at times where kind of where
the team can go or areas we can improve on.
But then I suppose the other side of that is
(03:46):
having a deep understanding of the game and background of
the game, and easy to understand with the amount of data,
what's important to look at and where you need to
look at, and to try and bring inside to the
team and help them improve.
S3 (03:59):
So can you paint.
S1 (04:00):
A picture for us? Maybe we'll see. Obviously we see
the coaches booth on TV and we see the laptops there,
and everybody seems to be looking at the laptops while
the game is progressing. Can you kind of paint a
bit of a picture for us? Just how data, I guess,
shapes your planning for each game and training sessions, and
particularly as you're going through the season? You know, imagine
you're not just looking at it from a player performance
(04:22):
point of view, but you're also looking at from the
opposition point of view as well, right?
S2 (04:27):
Yeah, definitely. There's probably a couple of key areas that
we'll look at. So throughout our week, opposition analysis is
obviously massively important. We'll generally work a week ahead of
the team. So it's like today on our day off
I'll be looking at the Reds who we play in
about ten days time, and then we'll have a meeting
with the coaching group on Friday and present, I suppose
the bones of the strategy there, and there'd be some
(04:49):
good robust discussion around how we go with the game plan.
And then from I suppose, the player point of view,
we'll then present that strategy Monday Tuesday to then have
a lot to do with that process. And then obviously
we'll review our own game, review our own players after
games training. Are we training the the plan that we're
trying to execute at the weekend? And then obviously from
(05:11):
an individual point of view is there are certain areas
we can help players with and definitely try to use
data as a tool rather than as a weapon. I
suppose in the past, or maybe at the start when
data analysis was used, might have been more just looking
at the negatives. But can you look at the positives,
can you see improvement and then try and help players
improve in that way as well?
S3 (05:30):
Yeah.
S1 (05:31):
So I guess if we sort of dig into that
a little bit further and I guess for, for our
listeners who are, who are probably not familiar with what
that actually looks like a big part of your role.
So I understand it is obviously looking at, um, you know,
video material and we'll talk a bit about that. And
that's pretty, pretty easy to get your head around. But
but how does that kind of mash up with the
(05:51):
actual data side of it? And I've heard this term
coding used as well. But how do those two things
kind of sit together? And I guess where does that
data come from?
S2 (06:00):
The main software that we use is called Huddle Sports Code,
which integrates video and data and which we what we
use every day and go to the usage on the players,
the ability to use it as well. And so coding
is effectively the tagging clips of the game. And then
layering on data labels to that, that are kind of
(06:23):
key metrics that we would look at. Or we feel
important as a coaching group to monitor. And so that's
part of our data. And then we have third party
data as well from Stats Perform who provide data to
all the teams in New Zealand. And we'll have that
data not just from our game or our competition, but
we can get data on competitions and players and throughout
the world.
S3 (06:43):
Yeah, and correct.
S1 (06:45):
Me if I'm wrong on this, but my understanding is
that the players themselves have a sort of a tracking
device in their shirts as well, and that forms part
of the data. What? I was aware of that from
previous years, but when I first heard about it, I thought, really?
S2 (06:58):
Yeah. So what kind of data tracking? All kind of
the physical metrics. That's more the physical performance side. So
that'll be Mark Bennett and his team and we'll generate
more out of it quite closely. There'll be a bit
of crossover between ourselves and them in terms of how
we we might integrate that into reviews etc. but for
the most part, we're just looking at game data, player
(07:19):
data more based around the actual game than the athletic
performance out of it.
S3 (07:24):
What about.
S1 (07:25):
Referee data? Are we are we all scream and yell
at the TV set? And I think last year's World Cup,
there was a fair amount a fair amount of that
going on, uh, especially with the TMO and so forth.
Does that form part of your part of the data
set that you're looking at?
S2 (07:39):
Yeah, definitely. Yeah, we've started to perform and just as
a player and director of player involvement and code referee
involvement as well. And we'll get all that data through
power BI. We'll definitely look at it each week, depending
on which referee we have and potentially just some of
the variances in types of penalties, they reward that kind
of thing if they're hot on offside or potentially causing
(08:02):
the scrum that we might need to talk to players about.
It's definitely a small part of it, but it can
be an important part, especially as you get into the
business end of the season.
S1 (08:10):
Yeah. What about the TMR? I don't suppose you can
get any stats off there, can you?
S2 (08:14):
No.
S1 (08:17):
I think you should if you want my personal opinion,
but we won't delve into that. Some years ago, I
had the pleasure of spending a very similar, um, podcast
with Troy Webber. Back in those days, he was talking about,
you know, some of the tools he was using and
also some of the challenges he was having around collecting
data and storing data. How has that evolved in your
time there? And I guess where's that heading as well
(08:37):
from a data management point of view? I mean, this
is an IT podcast after all. So I have to
ask a few questions.
S2 (08:44):
Yeah. No, absolutely. Um, yeah. It probably hasn't changed a
massive amount from where it was. Like the answers were great.
They did some great work in providing us with AWS
and all the other teams with quantity and quality of data.
And I suppose it's up to us how we how
we best use it. So that'll come into our power
BI reports too. I think it's Amazon Redshift. And then
(09:05):
we'll layer kind of layer our data on top of that.
So the data that we code and we'll go through
OneDrive and we'll link that into power BI. And then
kind of I suppose that's the bit of the dog
work through the off season, is to create reports that
then can just automate, um, each week once we're in
(09:27):
season or post training sessions as well. So there's not
a whole lot of added visualization of work because, yeah,
as you can imagine, during the season it can be
a bit time poor. So as much as that, we
can automate and be able to see and create insight
and give us focus points each week. It definitely helps.
S1 (09:45):
So how's that evolving with the coaches now? I mean,
one of the things I'm gleaning from this conversation is
that you're very much part of the coaching team, right? Yeah.
And in terms of your role, if I'm wrong on this,
you're on your second coaching team since you've been at
the Blues. Is that right?
S2 (10:02):
Yep, yep. And I suppose, you know, I first came
in with when Leon was head coach. And a lot
of the assistants have stayed the same since I was there.
And then obviously Vern and Jason Halloran and Greg Feek
came in, came in last year. So. And but yeah,
I suppose the evolvement there we go. And head coaches
are different around certain areas of what they want to
(10:24):
look at. So I suppose you're effectively trying to be
a second set of eyes for them. So having quite
a close connection with them, understanding what they want to
see is really important in terms of how we play
and our game model. So basically creating metrics that will
inform them to make decisions is is what's important. So
yeah that does change coaching group to coaching group and
(10:45):
being able to have a good honest conversations and trusting relationships.
Massively important.
S1 (10:50):
When I was going with that question, Adam, and I
guess putting experience back to your time in Ireland as well,
have you noticed between the different coaching styles, has data
played a different role in terms of those relationships? And
I guess is this concept of old school coaches versus
perhaps more modern coaching styles. What have you seen? Some
without naming names of course. Have you seen variances there?
(11:11):
And is that is that maturing?
S2 (11:13):
Yeah I think it's probably slow variances coaching coaching group.
But I think everyone now definitely sees value in it.
And for me it's again it's probably how you present
information to different people. It's not it's understanding that they
might just want to see spreadsheets or data in that form.
But can you show to them maybe understanding what the
data is telling you, but then show video clips, etc.
(11:34):
or some coaches will want want spreadsheets, they want graphs.
So it's probably just understanding preferences really, and how you
get your point across and how you can can add
value is the main thing.
S1 (11:44):
Yeah. So I find it interesting because you really, you know,
if I relate that to the way people use a
tool like power BI in the corporate space, you're telling
a story really, aren't you? You're trying to tell a story.
S2 (11:55):
Yeah, absolutely.
S1 (11:55):
And sometimes that could be relating to the opposition, or
it could be relating to an individual player or whatever
the case may be. And, you know, we talk a
lot about this business, about actionable data, right. And I
think probably more than most applications I come across in
this role, you're probably more actionable than most from the
point of view of you're looking at data and you're
making some pretty probably week on week decisions right around, well,
(12:18):
hopefully impactful decisions that hopefully will influence the outcome of
the game. Right?
S2 (12:23):
Yeah. So we'll definitely use tools like power BI to
to help us storytell and present that to to the
coaches and the players and on a week to week basis.
But also our GM of rugby in terms of recruitment, etc.
we'll have certain dashboards and metrics. We look at different
players and kind of key criteria of players in a
(12:44):
certain position of what we want to recruit, how do
we use data to to inform that. And until we
get through that process as well.
S1 (12:51):
Yeah. Yeah, yeah. So on that question of impactfulness, have
you been have there been situations or incidents that have
occurred over the last few seasons where, you know, without
without naming specific games, you're sort of quietly in the
back of your mind, patted yourself on the back and thought, yeah,
I nailed that.
S2 (13:10):
I suppose it's definitely a collaborative approach. And like the
team that I work with do a great job with
informing certain areas of the game and with the coaches
as well. So it's definitely I just want, you know,
come up with a game plan by yourself. It's very
much a collaborative approach across the whole team. So yeah,
there's certain times of the box when you've seen something
in terms of potentially space or a strategy that we use,
(13:32):
and it comes off that you can tend to get
a bit of a buzz out of it. But, um,
it's about the team doing well at the weekend. So
week to week, it's the main focus is that.
S1 (13:42):
You know, everybody's everybody's talking about AI these days. And um,
you know, you can't get through a technology podcast these
days without talking about AI. What are some of the
technologies out there that you're aware of that may impact
the sport, and particularly in terms of your role as
a as a data analysis? What are there things out
there that you see evolving that that could be really
(14:04):
impactful in terms of the data?
S2 (14:06):
Yeah, I suppose when you look at rugby, it's quite
new in terms of professionalism compared to other sports. And
obviously money is a big thing. But when you look at, say,
the NBA or English football, they have a lot of
tracking data. So tracking players every second, tracking the ball
every second and they range and range of data. So
and and there's there's been some brilliant work and research
(14:29):
going into that and how that's affected those games. So
yeah we are potentially tracking data and the availability of
that could be very interesting to us. I suppose kind
of machine learning and we do do a little bit.
We'll incorporate our into our power BI reports, some regression
analysis around understanding what the key metrics are to winning
(14:50):
certain games, etc.. So that's that's already a part of
our process. But as far as improving that and kind
of train those algorithms, even even more precise, because they
need that keep needing good data in the next level
of data is is the main thing.
S1 (15:07):
So my understanding is that from a data perspective, and
you touched on some of those sources a little bit
earlier on, my understanding is that here in New Zealand
that that is actually centralized around the New Zealand Rugby union. Right.
That's that's is that unique sort of internationally is that.
S2 (15:22):
And I think it depends on, on the unions probably.
I think Ireland and New Zealand are quite similar in
that regard with the franchises or teams being wounded. That's
kind of how our fear ends at AR. I think
potentially in France and England, when the teams are owned privately,
that's probably quite different. And I've seen teams have to
actually go out and have these relationships and build their
(15:44):
own systems. At the end of the day, there's an
awesome job at providing us with all the information we need.
And Jimmy Hamilton, the All Blacks analyst, is really helpful
in that regard too.
S1 (15:53):
And the other thing I was interested in was the
some of the video material we've talked quite a bit about,
you know, data and collecting data, but obviously video is
a major part of that as well. Talk us through
that a little bit, because you get to see video
footage that us mere mortals don't get to see on
Sky TV, right? So we get we get a very
controlled package of material, and it obviously cuts from cut
to cut. But my understanding is that you get to
(16:16):
see all of it, right, irrespective of whether the camera's
live or not. Right?
S2 (16:19):
Yeah, exactly. So we've got, um, four feeds from Sky
into our box. So it'll be that TV view that
everyone will see, and then we'll get a wide view.
Constant wide view, a constant view constantly behind the goal
and and then a tighter view and for more detail
around the rock and set piece. And then added to
that he jumped in. Well, we'll um video a reverse
(16:41):
angle and then a kind of wider view behind the
goal as well. So there's a really good relationship between
all the analysts across Super Rugby specifically. And we'll share
that footage with each other. And yeah, I suppose you
can get access to those for every game. Yeah. And
across the competition. So everyone has access to it. So
that's how you use it best. And the coaches put
(17:03):
a huge amount of time and effort into watching the
video as well. So it's a collaborative process still.
S1 (17:08):
Yeah. So have you ever had any situations where you
thought the TMO was wrong?
S2 (17:14):
Uh, potentially once or twice. Would I not generally be
there doing the best for the game?
S1 (17:19):
Yep. Hey, Adam. Well, there's probably a good place to
kind of stop and, um, look, uh, look, I found
that absolutely fascinating. And I'm really interested to see where
over the next year or two, where it all goes.
And it'll be interesting to come back to that. I
question again in a few years time and to revisit,
to see how that's how that's really impacted the types
of things you're doing with how many games you've got
(17:41):
to go this season.
S2 (17:42):
We have six games left plus a bye week. Yeah,
it's going to cost you just again.
S1 (17:47):
No pressure to add on for that reason. For that
reason I better let you get back to your data.
S2 (17:54):
Thanks a lot.
S1 (17:55):
All right. Great to talk to you.
S2 (17:57):
Cheers.
S1 (18:02):
Thanks for listening to another episode of Lifting the Lid
on Technology, brought to you by our partner, HP. I'm
Barry White, signing off. Until next time. Join us again
for more insights and commentary on the technologies shaping our future.
Popular Podcasts
24/7 News: The Latest
The latest news in 4 minutes updated every hour, every day.
True Crime Tonight
If you eat, sleep, and breathe true crime, TRUE CRIME TONIGHT is serving up your nightly fix. Five nights a week, KT STUDIOS & iHEART RADIO invite listeners to pull up a seat for an unfiltered look at the biggest cases making headlines, celebrity scandals, and the trials everyone is watching. With a mix of expert analysis, hot takes, and listener call-ins, TRUE CRIME TONIGHT goes beyond the headlines to uncover the twists, turns, and unanswered questions that keep us all obsessed—because, at TRUE CRIME TONIGHT, there’s a seat for everyone. Whether breaking down crime scene forensics, scrutinizing serial killers, or debating the most binge-worthy true crime docs, True Crime Tonight is the fresh, fast-paced, and slightly addictive home for true crime lovers.
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com