Once you've selected load, it
will load a couple of seconds. It will just check the quality of
the data, that everything is okay. And there you go. What happened now is that
he's connected to this Excel file that you stored locally. And you can now start to play around. So that's how quick you can go from
Excel to connect your data in Power BI. Literally a couple of seconds. So I'm joined today by Ciaran and
Johannes from Sport Horizon who are going to tell us all about getting into
these kinds
of tools and also provide us with a demonstration of how we might
use this in sports science and talk a little bit about their course that
they provide through Sports Horizon. So have a look below as well because
we're going to be sharing some links that get you 15 percent off all of
their courses that they have available. So, guys, thank you very much for
sharing your time and your expertise. Thanks very much Jo. So I started off as a Gaelic football
player in my, my native Ireland. Played with
my county and that
was really my big introduction to sport and sports science. Did a degree in sports science in
University of Limerick and coached a lot. So my kind of first job was
really in as a coach and as a development officer, a mix of sports
science and coaching and playing. I then came to London, started
a internship in QPR in a football club in West London. A club that actually I've, I support,
strangely I support, support in Ireland. My whole family do because my parents
lived in She
pherd's Bush back in the 60s and 70s before returning back to Ireland. And then also did a Masters
in Strength and Conditioning. So really it was as a sports
scientist with QPR over the last decade or more really. I had a little bit of a sabbatical
over in India working in the Indian Super League with Curla Blasters under
Peter Taylor and Terry Phelan, which was a brilliant life experience and a
challenging professional experience. At all stages, it was more on the
sports science rather than the
S& C. I think my work with QPR and at different
times then, as I mentioned, as regards to coaching, I coached and managed the London
Gaelic football team, which participated at national level back in Ireland. So that kind of gave me a nice,
holistic view of performance. So it wasn't just sports science, it
wasn't just coaching, it wasn't just data. It gave me a nice view. And then in the latter years with
QPR, I thought, you know what, there's something that I need extra,
you know, we were gat
hering all this GPS data, and it's like, okay, what
are we actually getting meaningful insights and impacts of this data? In the intervening years then I
started a PhD in collaboration with Northumbria University and Queen's Park Rangers on
neuromuscular alteration and impairment as a result of youth training. Thankfully, I submitted that in a
couple of weeks ago, so I'm just waiting for the viva on that. Johannes, I'll Hop over to you
before we speak about the kind of Sport Horizon and specific
stuff. Thanks, Ciaran. And obviously thanks, Jo, for inviting us. We absolutely love the data and
where this space is heading. I haven't always been in this
space in comparison to Ciaran playing Gaelic football. I played real football, I would say. But I wasn't really good
in this real football. So I thought, you know
what, if I can't play it. Maybe I can study it. Started studying like sports science. And as many people probably recognize
with Norway, it's a winter country. So we are very good
in endurance sport,
so I thought, but if I'm going to work in football, I need to go somewhere else. So I went to England to take a Bachelor's
in Science and Football at John Moores. Started to get into the clubs,
like the link between John Moores and the clubs are very, very good. I always had like the physiology, the
biology interest in the very beginning. So I did my, I did sports biology. I did the science behind
it, the performance. I did later a master's in
strength and conditioning. So I
always had that interest in
physiology and, and was working for a fitness coach or strength and conditioning
or whatever you want to title it for a number of years in, in England. And also later in golf and in
Aspire Academy when I was there. As I sort of went through that
journey of these different roles and working on the pitch and being with
the team, there was always this. this interest in the data side of
things, and that interest sort of just increased and was kind of in parallel
with thi
s increase in amount of data as well, because when I was in these
early internships, I thought, oh, but a lot of my job was to collect all this
data, but where is it really going? What are people doing with all this data,
which was like a question I didn't really felt was really answered, like the amount
of collected data versus the amount of data being applied , I felt there was a
mismatch in those early days, and that really got me interested in, in this
space of Tableau and Power BI as potent
ial solutions to be able to communicate and
take advantage of all that data collected. So in the last five, six years, it's
been mainly data, obviously in parallel with other things, but now it's all
data not being on the pitch anymore. And that's where we sort of also came
over into the Sport Horizon side of things that, okay, there's definitely
a space or some gaps here that we. Potentially can help, help people with. So now it's, it's all data, my
passion, so absolutely love it. Thank you bot
h. I think the reason I wanted to chat
with you is in part because you're both coming from very practical backgrounds,
playing, coaching, sports science, and I think there is this interesting,
kind of debate, I suppose, around do you bring in data scientists who
have those real specialized skillset? Or do sport scientists try
and develop these skills? And I think you two are really
great demonstrations of that, of upskilling in the areas of data
analytics and visualization. So, that brings us to
Sport Horizon. How did you two first get connected,
and then how did it turn into what we see and are going to chat
about today in Sport Horizon? A couple of moments kind of helped
me along the journey to kind of meet Johannes, and come up with
the concept of Sports Horizon. The first one was going back a few years,
where I was pulled in from the office into a retain and release meeting of an
under 18 player by the academy director and head of coaching and head coaches
and head the question was
, how has this player performed over the season? So I started like frantically
pulling out GPS reports and, charts from this game and that game. And I just, I came out of the
meeting feeling that Maybe I did that player a disservice. I don't know exactly. That player was subsequently released. I'm sure it's not off the basis of
what I presented, but I just felt that it needed to be more comprehensive. It needed to be, like, to be able to drag
data in, longitudinal data from across the season, or
multiple seasons, and
to present them with, okay, here's some real performance data that can actually
give some insights into the performance and the development of the player. And that was the kind of
moment for me where I went, OK, Excel is not cutting it here. You know, these kind of individual
charts and it's a little bit messy. And, if there's a row out of place
or whatever, it's difficult to change them and edit it going back over time. But that was the first moment
where I thought, OK, w
e really, really need Power BI. The second moment then where I was with
the QPRB team up in Manchester and we were about to play Man United the next
day and it was kind of a eureka moment for me where I was doing up the weekly
reports still in Excel at that point, even though we had kind of made moves
to transfer over a transition to Power BI and I spoke to a good friend of mine,
Shane Malone in Ireland, who's worked with the GAA, Irish Rugby, amongst
other teams and his lecture as well. And he
on the quiet showed me some
of his dashboards and reports. And I was, I was just blown away. I just thought, wow, this is, it
just visually looks so beautiful. The insights gained, the multitude
of players across days, across weeks, across different variables and metrics. And I thought, okay, this
is what we need to do. So I used my parental leave and
over off season to build out those first dashboards and reports and
we used that then for the next probably year and a half in QPR. And then I me
t Johannes on a world soccer
Congress in Coimbra in Portugal, where I was presenting a poster and Johannes
was just freeloading there, having a good time and we just started his talk
and he, he looked at my reports and he said, Okay, yeah, they're good, level,
and he showed me some of his ones, it was another level, another step up there,
kind of advanced Power BI and Tableau, and it was probably at that point where,
linking back to your point, Jo, where yeah we felt that coming from practitione
rs,
OK, you can have the data scientists who they might help with the overall
structure, the club structure of the data channels and everything like that. But really, you need people who
have practical experience and knowledge from the grass to the
insights to be able to communicate with the players and the coaches. And that's where we felt that really
there was a space there missing, that there was a lot of practitioners
around the world who wanted to utilize Power BI and Tableau. But when you
start looking online, there
are YouTube videos from financial women and men who are showing how to use Power
BI in Tableau, or, you know, there's a lot of different business orientated
people who are showing how to do things, but there wasn't really anybody in the
sport or the sports science sphere. So I guess that was the point
at which we said, okay, maybe we can start building something
ourselves and using it ourselves. just want to add to that. I felt another thing that is important
to ment
ion is that I have, I completely understand that the roles that people
have in the clubs is extremely hectic. Like, the day to day activities in
the clubs are full speed, like, you barely have time to eat your lunch
before the day is over, there's a new game, there's a pressure you
need to deliver and everything. And for you then to spend 10 hours
on a YouTube video that's extremely general, that is not covering Thank you anything close to what you are requested
at and are under pressure to deli
ver. I can understand it's a challenge because
it was definitely a challenge for me because I had to sit on YouTube and try
to understand how on earth I am going to calculate acute chronic workload ratio. I tried to speak in the forum. I tried to ask, yes, but, and
the guys just have no clue. What is this ratio? The specifics of the courses that we
traditionally have seen are very general, and it needs some time to sort of
translate that into your environment and what you probably are requested
to build. So it was here we really felt,
OK, why don't we make the course specific to the needs and the
roles that people are in clubs? Because one thing is to use Power BI or
Tableau, but another thing is to use Power BI and Tableau in your space with the type
of questions you would answer with the type of data that you normally are given. I think that was a space also that
we wanted to really try to fill. So if you just had three hours on the
weekend, that is actually enough to go from having
nothing to have your first
couple of reports that you can show on Monday morning without having to spend
all the weekend watching something that might give you an idea where to start. The nice thing actually as well
is that on the courses that we provide, it really does go from like
how to connect through SharePoint, through OneDrive, through Dropbox. And like we say that, okay, this
is what we think is the optimal, this is the best way of doing it. But we understand that in a lot of clubs. They
're still using Dropbox, you
know, they might even be using localized laptops for their data. And each kind of module is both
a team and a report or dashboard. So like at the end of each module
you can produce this really nice report, but also it covers a team. I think that's why I think this is so
appealing and why I wanted to share it really is because you guys are adding that
context, that relevance to when people are learning, they are going to be learning
with the actual kinds of data, the
kinds of questions that they're dealing
with, which is going to be so much more meaningful and useful than doing, analysis
on flower datasets or weather datasets. It's really meaningful to them. We're going to do a bit of a demo
as well and talk through how to actually get started, but let's
almost start at the very beginning. You've spoken about how
ultimately in sports science we kind of max out Excel, right? And this doesn't
necessarily replace Excel. It's still going to be important to,
as a
younger practitioner, develop the skill sets in Excel to learn about
pivot tables and formulas and that's going to set you up for these next
steps that are Power BI and Tableau. So can you guys maybe explain
to those who might not be aware what these tools actually are? I think you're absolutely right, Jo. I think you framed it nicely
because it's not the fact that we're completely removing Excel. The way I see it is that we've
just changed the role of Excel. So in my job before, if we go
back
we do everything in Excel. have the data there, we collect it,
we input it, we transform it, we wrangle it, we display it, we share
it, like we do everything in Excel. Now I feel like Excel has changed
that role and we sort of divided it into Excel being where I personally,
speaking from my experience, where I store the data, not always, but a lot
of people are storing the data in Excel and then using Power BI or Power BI. Tableau, these tools to communicate
their insights, to, to share their da
ta, to display insights to the
coaches and do the analysis there. That's effectively what these tools are. These are business analytics tool where
you can communicate, if we put it very, very simply, communicate your insights
and your data and your analytics. I don't want that people should
completely go away from Excel. I think there are some very useful things
in Excel and we need to be aware that also a lot of the companies that are collecting
data all of them export to Excel. Obviously now y
ou have a lot
of the a lot more have the possibility to connect to an API. That's a slightly different thing
that requires more skills in Python and R and these type of languages. So if you still just are at the other side
of the journey, to store it in Excel is a very convenient and simple solution. But what I found when I tried to
have this all in one solution in Excel, and the reason why I sort of
shifted over was, It's multifactorial. I, I remember I was trying to
create an Excel document fo
r maybe five, six years ago to all
the clubs in Norwegian football. So we're speaking top division
clubs, so 30, 40 clubs. I needed to create an Excel file
where I could input the player data to show the game cycles of the players. And I thought, okay, perfect. No, no issue at all. I've done quite a bit of Excel, you
know, you have some VBA coding, you can add some function when you press
here, this happen and really maximize, like a really maximized Excel. And then I was going to share all
this
with everyone and one guy's reply, ah, sorry, but I have Mac. This function isn't working on Mac. Okay. No problem. And then next, I pressed the wrong button. I deleted all the functions are,
and then it just came rolling in. So that was one of the reasons and lead
me over to why I sort of shifted over. I feel like the possibility to
collaborate across the organization, because it is a Microsoft
solution, you can put it in Teams. I recently did a presentation where I
integrated Power BI into Po
werPoint, so I was having an interactive
presentation with someone else, but can I have a look at my club? and in PowerPoint, because it's a
Microsoft solution, you select the club, you change the filter and boom,
your club arrived live in PowerPoint. You don't need to go anywhere,
so I feel like because it's a Microsoft solution, especially with
Power BI, it's easy to integrate. Now with the AI features, there's
a lot of AI features coming into Power BI, and I guess the big one
for me was just
the ease of use. Like it's very quick to go from having
just Excel and I will show in the demo later on how quickly you can go
from having A raw data file in Excel to have your first chart where you
can do a lot of different things. Just to take a step back as well from
an applied practitioners point of view, we're gathering so much data from
different sources, GPS and VALD and performance data and maturation data. Um, and your ultimate job is to
become more efficient, to quicken the process, an
d then to gain
more insights and communicate that to the coach and to the players. Like, that's a very kind
of simple journey of that. And the use of Power BI
and the use of Tableau will drastically quicken that process. So, from our point of view, we're saying
to practitioners, then, that Look, you don't need to spend two hours on dropping
in the data, filtering it, creating the tables, the charts, creating the reports,
that you can actually make that process so more efficient, so that you can
have
your report, your dashboard created in, you know, a matter of minutes, in
a really good case, and then you can spend your time on going into the gym
and making sure that players, you're engaging with the players more, or
spending more time speaking with the coaches, or planning individual programs,
or talking about the next day's session. So it's really making the
process more efficient. And then sometimes, it's quite
a trendy throwaway remark to say that, oh, it doesn't matter how
It's how
good your report looks. It's how you communicate that
with the coaches and the players. And in part that's true. In some ways it's not about making it look
amazingly fancy and everything like that. But, and There's a lot of science
behind your communication strategies and colors and how the data is displayed
and so you don't have to make it look amazingly fancy but again you want
to make it look nice and engaging and gain insight so that the coach can kind
of say oh yeah actually that that's qu
ite an important point there isn't it .
So what I'm hearing then essentially
is efficiency and effectiveness, right, which is what as sports
scientists we're all striving for. Hopefully we save some time and make
our own workflows as efficient as possible as well as for those around us. But then making sure that, that, that
data, the reports, the communication is as effective as possible. Okay, so now then, getting started. As I said, we had
everything stored in Excel. We had all the charts, the
tables. It was quite an inefficient process. At the beginning, we were still
Housing all our data on, on Dropbox, on Excel, exporting across to Power BI. We had built our charts, our tables there. Johannes will show in a second,
maybe that that is definitely not the the most efficient way. So I suppose for somebody who's
trying to self learn like that in the way that that I did over a
number of years is definitely not the best way or the most efficient way. If I had engaged with the courses tha
t
we're doing I probably would've cut out about 18 months of learning, I suppose. Hmm. But I didn't have anybody to kinda show
me, okay, this is the gold standard, this is the, the best way, let's say. But I suppose that's how
we've tried to kind of be much more efficient and provide
users and practitioners with like here. The best steps are the quickest
steps to get you from 0 to 10 on Power BI or Tableau. Personally the way I
learned was little just. Download, open, and try. I literally just w
ent home. I got a student license. I opened the, the the software. I connected to some data and I just
thought, okay, what happens if I do this? And I literally just tried. And that is, I think
that's still important. People definitely just need to dig in
and play around and see what you can do. But I think it's also important
to at least be familiar and understand the basics. Because if you, if you don't get the
basics, right, you will come to sort of one level where you're sort of a
bit stuck
because you don't understand the basics, which doesn't allow you
to sort of go to that next level. So I'm a bit of understand the basics, get
them, get to know them well, but also just keep playing around, like in parallel,
there is always like this continued development, things are changing. So if I'm just in Excel and I'm
thinking, should I get started? I just want to show you how
quickly you can get up and running. So I believe, Jo, you will, you will
share this document with the people. So i
f you want to try, Jo will share
with you that, that Excel document file. So there's literally no excuse. You only need to download the
document, download the software, if you don't already have it,
and then just follow these steps. And you can build a session
report in just a matter of. And I just want to be clear, like,
obviously we cannot cover everything, but this is just how you can get
started to play around, to try and fail and actually build something. So I would just share my screen her
e. So I would now just assume
that you have downloaded. the software, and you also downloaded
the Excel file that Jo will provide you. So this is some data that's
collected from a GPS unit. So there is some GPS data for
a team for a couple of months. So when you've downloaded the
software, it will just come in here. So this is how it looks. You will then Simply, we'll go straight
ahead, no fussing around, we'll just go and get the data straight away. And then I will explain in more detail. So wh
en you come on here, make
sure you are in the Home tab here, and you select Excel. Just browse to the folder that you have,
so I have stored the data and the file. Select the file, and you select Open. This will then load a little bit. And it will ask you which sheet
in the document would you like to connect to, because you might have
different tabs or sheets in Excel. We only have one, so we'll just grab
this one, and we'll select load. Once loaded, If you selected load,
it will load a couple o
f seconds. It will just check the quality of
the data, that everything is okay. And there you go. What happened now is that
he's connected to this Excel file that you stored locally. And you can now start to play around. So that's how quick you can go from
Excel to connect your data in Power BI. Literally a couple of seconds. What we will have then
is that a data pane. This is where you can see your table. So we just selected sheet one. If you press the arrow, you can see
all the columns we have
in our data. For you to just understand what
we're speaking about here, I'll just come to the view on the left here,
which is called the table view. Currently, we are in report
view, where we build the report. We have another one that's called table. This is where you just can
have a different look on the data we just connected to. So this is. Very similar to what we see in
Excel, we have a tabular format, meaning we have some columns,
and we have some rows of data. You can scroll down, you can
find
a column you would like, and you can play around a little bit. If you want to filter some
data, you can do here, and say I would like only a given day. You can select that and
you will get that data. It's important to notice that
this will not change the data set. This is done in a different place
that I will explain later on, but this is how quickly you can play around
and see a little bit of your data. So normally you would come here
if you're unsure about what you've done for a given ca
lculation. You can come here, filter the data,
and you can see, ah, okay, that is correct, or no, that was not correct. So we've seen how to connect. We've seen how we can have a
look at what data we have on the right in a table and the columns. We then have what's called a
visualization pane, and this is the beauty of Power BI because you have a
lot, a lot of different ways you can communicate and display your data. And there's also a community
building a lot of visuals, which is really, really
cool. Get more visuals will give you a
host of different alternatives if there is something specific that is
not already here that you can add. But if we are just keen on creating
a session report, and you can do a session report in many ways, but here
is one how we can do it in three clicks. Select stacked bar chart, you pull
it out here, and then it's saying and giving you options what you can fill in. We would like maybe our player name. That's always nice to see who did what. We can put tha
t on the y axis, and you
can take the traditional total distance that we love, as an example, and we pull
that on the y axis, and there you go. Literally, in three clicks,
you can create A visual. There is a lot of things you can do
with these visuals, and I encourage you to just play around here. What happens when I select this one? What is this? What does it mean? Okay, it means that. Just play around a little bit. This is only to get you started. How do you come in here? If you want to duplic
ate this, CTRL
C and CTRL V, and you can change the metric, and we have another one. So that's how easy you can create a chart. You can modify the chart. Different types, move it
around, and there you go. The last thing I want to show you,
in order to get started, now we're taking all the data, but you might
want to have a look at just a given session, and that's nice to know. Well, we have another one called Slicer. We can pull in the Slicer, and he's
then asking, can you please give me a field
that I can slice the data with? Let's say we take the date. So we pull in the session date. And if I now just drag this one, you can
see the data is changing automatically. And it's applied to both, so it's super
easy now to start filtering your data. Maybe you want to change this a little
bit, and you want to have a dropdown instead, so you can select one date. And there you go. You can select the given
date that you want. You can do the same to add more filters
if you want players or any othe
r things. You can modify colors. So that's essentially
how you connect to data. Select Excel, add a chart, pull in what
you would like the chart to display. And you have built your
first session report. You can, of course, add the background
colors, add some titles and everything. But in order just to get a feel for,
without being afraid of anything, because it's very quick to get started, you
have now the file, you've got the link to download, and I just encourage you
to play around with this,
and obviously if there's any questions, we are more
than happy to help out, and that's how to get started very, very quickly. It looks a lot less scary and it
looks a lot more just like Excel. So again, reiterating the importance
of those initial skill sets in Excel that then transfers over
to these kinds of tools as well. If you are familiar with Excel
before, you would find the sort of change over much more convenient. At least I found because they're
still in the Microsoft solution. So Micros
oft understand, OK, the
logic there, it's probably nice to apply, so it's not completely new. So you're definitely right. There is a lot of similarities. Yeah, the other thing I was going
to, an additional point I was going to mention, we, we, we won't cover
it today, but it's, it's in the courses, is that you can do a lot of
the manipulation of the data and the analysis in Power BI, so you can set up
structures within, let's say, the backend of Power BI before it's visualized. And the beauty ab
out that is that
It can take out the chance of error. You can just drop in your CSV files or
your Excel booklet or whatever and even if there are little errors in that, if
you've manipulated that data in a correct manner and set up rules and everything
like that, it just takes out that chance. So I think you've shown here then the
clear benefit of experimenting, which you've both spoken about, but clearly
anytime we're trying to learn, then some structured learning is a benefit as well. And as y
ou guys said, I think the
unique approach that Sport Horizon and your courses are bringing
is that relevance, that context. So I wondered if you wanted to maybe show
some examples of what kind of example dashboards or reports going through the
courses people will learn to create. Definitely. So I guess for the level one course
that we have, we cover a lot of these basics, how to get connected,
how to modify your data, how to build the different visualizations. So you really upskill on and gettin
g
confident in using this software. Then we understand there are a lot
of people who are sort of at that level already, that maybe are already
in Power BI, who are confident with playing around a little bit, but what
I've found is that sometimes you hit a little bit of a plateau at that stage,
because you maybe haven't done some of the fundamentals at a high enough level,
and I think, and I think it would be useful to share a little bit as well. Some of those things that I've found,
if you maste
r these couple of things, you can really sort of take that next
bounce and your next step in Power BI. So I can show a little
bit of that as well. So if we cover that basics, if we come to
sort of a more advanced part of Power BI. The data modeling is maybe one
of the skills that I felt people underestimate the value of. A lot of people are trying to
learn complex DAX and they try to do different things, but I've felt
that If you manage to master the data model, you can really upskill. And this
is something we really
try to explain in plain, English. What on earth is a data model? Okay. It's two tables speaking
together and you have a model. It's not more complex. Let's just. Let's make it simple for the people. So if we come in here, you
can see this is a data model. So that might look a little
bit scary at the moment. If we come back and just show the
alternative model that we just built, I think that's nice to show. This is the data model we have. It's literally just one table. So w
e see the table, we just input it. And that gives us a table. If we had another table, and we
connected them together, we could say, okay, this is our data model. It's two tables speaking
together in a given way. And that brings us over to relationships. The way they speak together is
what we call a relationship. And you can tell one table to say,
I only take data if you have this. Or you can say, ah, we take
a little bit from each other. Or the opposite way around. So you have different types o
f
ways these can speak together. And if you manage to understand how
Power BI like the model to be, because Power BI have one structure and one
way it prefer that you build the model. And we call this a star schema. So it should be some tables in
the middle with some stars around that you can use for filtering. And when you understand how to do that. You can really reduce the amount of
complexity for your DAX calculations. So if you're not confident with DAX,
because it's not an easy language, w
e need to be honest, it's not the easy language
to learn, to use and write code on. But if you understand the data model,
you can reduce the complexity immensely. So what essentially is happening here is
that we We've created a player report, a player dashboard, something that
some, probably many are looking for, where you have a lot of different tests. It's the same athlete doing the test
every single time, but they might do different time points, different
tests, and you maybe want to compare
the different tests against each other. What happened last time to this time? So what we create here
is just a player table. So we have all the players in here. We have a date. So it's essentially just all the dates. And then we just put the endurance
data, we put the sprint data, we put the countermovement data, and we just
put that around these two tables. So when I select, if I select Jo here,
that you're one of our players, I filter Jo for the endurance, for the sprint,
for the countermoveme
nt jump, and I say I only want Jo for the last year. No problem. I go in the date table and I
say give me the last year for Jo for these three tables. So I think understanding how you can take
advantage of a good data model is really something that I felt been undervalued
when people try to do something quick. And I think that's why it's important
to explore and do everything, but also have that structured learning. At the same time, so you can understand
these basics because that's when you rea
lly can can bounce off so
that that will definitely highlight. If you want to explore something when you
are in Power BI, explore the data model and also the button called transform data. So this is the power query editor. So, this is essentially where you can
create these tables for the player ID, for the comparison between data,
and you can do some modifications if you want to create a ratio,
or some comparison, or anything. So, explore the data model,
relationships, and the query editor. Once
you master those, you are in a
really good spot to create visuals like this, where you compare players of
your team against all the other teams historically, where you can add filters
and, and do a lot of comparison depending on either the generation or position. Maybe you want to compare all
the goalkeepers that you have on countermovement jump, or so when Ciaran
have that discussion about the player, should he be selected or not, he can
say, well, this player, compared to all the players that
we had in this
position at his age, with his maturation status, he's actually quite quick. And there is maybe some hidden potential
in this player that we need to consider, maybe not making changing the decision, at
least you have a more informed decision. One of the questions we get
asked a lot as well is should you go with Tableau or Power BI? And I think traditionally Tableau
has been viewed as the slightly more advanced software solution
and slightly more intuitive. I think marginally looks
better
and I think still at this point looks a little bit more cleaner. It's like with Apple, it's like with,
with Microsoft, any of these huge multinational companies, when they
start putting effort into a solution, like it advances at a crazy rate. And we're probably seeing a little bit
of that with Power BI now, like Power BI is a native Microsoft solution and app,
and they're putting a lot of effort and the other thing as well that's currently
happening is obviously the, uh, all the AI solu
tions, like with the copilot and
everything like that with Microsoft. It's just meaning that the advancement
in the solution is just going, you know, on an upward trajectory. It's worth mentioning as well,
is that I think, Johannes, we would say Power BI is a little bit
easier to master at the beginning. Just the functionality of it so going
from Excel to Power BI is a little bit easier a step than to Tableau. So it's not like we push people towards
Power BI, but I think a lot of people just hav
e Power BI as part of their
Microsoft suite of apps in Office 365. Brilliant, so I know you guys are working
hard to always add courses as well. At the moment it's Power BI for
Sports Scientist Level 1 and Power BI for Sports Scientist Level 2 and
Tableau for Sports Scientist Level 1. So what we feel is that as the demand
grows, as more people go through the Tableau Level 1, we'll add on
a Level 2 then, the next level. But at the moment, and Jo, you're probably
seeing it when you're going around
to clubs around the world and interacting
with organizations, the hot topic at the moment seems to be Power BI and
that's what people are, are looking for. I guess in the near future and the
medium term, like we're looking at first of all, Power BI for S& C coaches. So specifically looking at gym
loading, maturation based, performance data as well, fitness testing. There's other mini courses that we're
looking at as regards like Performance Analysts, because obviously they're
gathering so much
data as well and performance and technical data, and it's
it's nice to have that they can look at our courses and improve their Power BI and
Tableau skills massively, but what about specifically taking some of their data and
making it really relevant and specific? The other thing is that we're looking at
is a membership model whereby instead of just purchasing a course that you can sign
up to membership or like a monthly rolling membership and then every month we upload
videos and upload solutio
ns about okay. This is how you do create this report or
what are the users and practitioners kind of problems and how can we solve them. And then to create a community of
practitioners then where we all learn from each other, which is
the kind of the ultimate goal. and also some kind of
service consultants as well. So like we are currently already
working in some football clubs, whereby they've come to us and said, we want
to solve either this little specific issue that we're having with our dat
a
analysis and data visualization, or also we're working with a club where
they're working with They're saying to us, okay, what we're doing now is
great, but we would like to do X, Y, Z. Obviously that's a bigger build that
either we can come in and just create it for you and leave you with it, show
you how to use and leave you with it, or we build it for you, we maintain
it, or a kind of a collaborative agreement whereby we show you how to
build this, you create it, but also we're there in the
background to kind
of help that process, at all stages. You guys have kindly offered
15 percent off for anyone who's watched this video and is keen
then to dive into your courses. So we will put in the description
below the relevant links for all the courses you mentioned. And as you said, lots more
on the horizon as well. No pun intended. For people who want to know
even more about Sport Horizon. as well as you two individually, where
is the best place for them to go online? www.Sporthorizon.
co. uk is our website, so sporthorizon. co. uk, and I'm sure that'll
be in the notes from Jo. You can email us at info at sporthorizon. co. uk. We've a bag full of free content as well,
actually, on the website and people will find that through LinkedIn posts as well. And we just feel that where we can give
out a lot of this free content that people can engage with and how to create some
really cool and interactive dashboards that Johannas has made from like the
Women's World Cup recently in Aus
tralia and New Zealand and you can get an
opportunity to play around with your data and kind of have a bit of fun with it. So do have a look at that as well. Best social media way of contacting
us is through LinkedIn, definitely. So there is Sport Horizon UK
handle on Twitter, or you can find me, Ciarán Dealy, or Johannes
Martinhusen on LinkedIn as well. I suppose LinkedIn is kind of
our main social media channel for, for this business. We've put up a series of posts over
the last year and a lit
tle bit. We've only been in existence, you
know, about 14 months, I think. And already just the interest
we've had, not just from football and from other sports, but around
the world has been incredible. You know, we've had people from
Africa, Asia, South America, North America, Europe, obviously UK,
plenty Ireland flying flag as well. You know, it's been, it's been great. And the nice thing is like, we just get
people just dropping in a direct message on LinkedIn and we can chat there and also
anybody who does our courses signs up to our courses they join a little WhatsApp
group as well for Power BI and Tableau. It's quite cool actually, so we will
just post some interesting things we find online about Power BI or data analysis
or Tableau, but also we've got into the habit now of users have actually posted. First of all, they posted some issues
they have with their data and OK, how can I solve this issue and not
only we are coming back, but other users are coming back as well. So we'r
e creating that community
of practitioners with solutions and probably my personal favorite. Then is some of the users post actually
little screen grabs of their dashboards and reports and we can kind of go. Oh, that's really cool. Actually, it looks great and they
often ask for feedback and we can give little tips and feedback as well. I would definitely encourage people, one,
to go on the Sport Horizon website because you've got some examples on there and of
course more information on the cour
ses. And I would certainly encourage people
to follow both of you on LinkedIn because I do think that you both post
some really interesting content on there as well as tons more examples of the kinds of dashboards as
well as your real life kind of stories and experiences with it. Thank you guys very much for your time,
for sharing your, your stories, but then also the demonstration and, and
hopefully this will help viewers feel perhaps a bit more confident going
into this upskilling in these are
as and becoming hopefully more efficient
and more effective in their, their data and their sports science processes. So thank you guys, guys both very much. Thank you, Jo. Thanks a lot.
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