Episode 10: NFL, football, and data analytics, an interview with Shuler Cotton a data analyst with the Buffalo Bills
Episode 10 features Shuler Cotton, a data analyst for the Buffalo Bills. Shuler analyzes the football data from the team and players to answer questions and create automation. Tune in to hear what Shuler did to get a job in an industry he loves and what it is like working for the Bills.
(funky music) - This is "Buffalo State Data Talk," the podcast where we introduce
you to how data is used and explore careers that involve data. (bright music)
Hello, and welcome back to another episode of "Buffalo State Data Talk." I'm your co-host Heather Campbell. - And I'm your other cohost, Brian Barrey. And thank you for joining
us for episode 10.
- Today, we'll be
talking to Shuler Cotton, the data analyst for the
Buffalo Bills football team. Before we jump into today's episode, we wanna share with you our
summer release schedule. This summer, we'll be taking a break
from our regular schedule and providing a deep dive into
everything you need to know about getting and
succeeding in an internship in data science and analytics. These episodes will give you information
about whether a data science internship is the right route for you, including how to find an internship, everything you need to know about applying and acing your interview,
and how to be the best intern ever. Many of these tips will also be helpful if you're searching for a job. We hope you'll join us for our mini-series all about DSA internships,
but if you love our regular content, don't worry because we'll be back to our regularly scheduled
programming in the fall. Now back to our interview with Shuler. - Thanks for joining us today, Shuler.
- Thanks for having me, Brian and Heather. It's a pleasure to be here. - So could you start us off by giving us a general overview of the work
that you do for the Bills? - Yeah, so I'm a data analyst who supports
the football operations
of the Buffalo Bills. I support coaching, doubting, and sports performance primarily, although our department
does handle requests from every other department
on the football side of the Bills. So we handle the requests
from those departments, but also do projects based on
our own intuition analysis. And my job is to bring our data to life and make it actionable for our users
and just make everyone's
lives easier on the team by helping them do their jobs more quickly and with better information. - Excellent, so now we have a
bit of an idea of what you do. Could you tell me about what a typical day
or a typical week looks like for you? - Yeah, so it depends
on the time of the year. During the season itself, I'm primarily helping the staff prepare for upcoming games.
During the off season, I'm
helping the staff prepare for some of those bigger
milestones, such as, you know, the combine, free agency, and the draft. Every day is unique, especially when you're
managing ad hoc requests
from all these different departments. You might be meeting with
the dev team in the morning, and then you have to talk to a coach, and then you're primarily
working by yourself in the afternoon.
So it really is a little
bit of everything. - Could you give me a quick example of what kind of those requests are? You don't have to say anything specific, but, generally, what kind of
data are you dealing with?
- Yeah, it's all football-related data, anything relating to
the team or the players or any other aspect of the staff. So, yeah, it's just... It's primarily for...
Taking the data that we have and answering questions that the coaches or the scouts may have, and also doing longer-term
projects as well, studies... You know, sort of like
research and development,
but then also like
functionally within the team, like, contributing on a
day-to-day basis as well. - So do you work in a team of
people to analyze this data, or do you work more by yourself? - Yeah, so I'm within the analytics
and application development
team at the Bills. I work closely with our
director, Luis Guilamo, as well as our software developers, Warren Zarila and Raymond Alonzo. And we kind of function as, like,
a sweeping arm, if you will, across all the departments, developing our analytics solutions. - So you mentioned you had some people more on the software side,
and maybe some people more
on the data analyst side. Is that kind of how things are split up? Do you do more of the... You know, maybe programming
side of things, or... What specifically do you do versus them?
- Yeah, so Warren and Raymond primarily are developing applications. I do use those applications, but I'm also providing
analytics into those... Into those applications.
So, I mean, I do programming, but in terms of, like, large
scale software development, that's not primarily my focus. - All right, and how would
you say your time is split between working with
those people in your team
and spending time working by yourself? - Yeah, I would say, depending on the time of
the year, that varies, but, on average, I would
say 80 to 90% of my time is spent on driving individual
tasks to completion,
you know, outside of
brainstorming or review or... You know, we have daily
stand-ups in the morning. You know, I'm expected to
complete my work individually. And you know, when I first got here... When I first started the
internship with the Bills,
that wasn't always necessarily
the case, you know, asking questions and really having to
learn a lot on the job. But, you know, primarily now I would say I'm doing most of my work by myself.
- Shuler, I know that you
briefly touched on this in the last question, but what kind of data does
your team collect and use? - Yeah, so we use data from
a lot of different places, primarily from the league...
You know, the NFL, that they provide. We collect data internally as well and then data from third-party sources. Most of my job is analysis
and not collection, although I'll create some small things
here and there if needed. - And I'm not sure how much you can go into detail about this, but what is the volume of
data that you work with, and how do you store that data?
- Yeah, I'm not exactly
sure of the specific volume. It's a lot. And primarily it's stored in servers that we have on premise. - Okay, and once you've
collected and cleaned the data,
how do you analyze the data, and are there any programming languages or software that you use? - Yeah, so in terms of
our technical stack, we primarily use SQL Server for, you know,
data manipulation, database operations... We use R for data modeling and then some other scripts that we write. Tableau is another big one that we use for exploratory data analysis
and some reporting as well.
And then we also use Telerik Reporting, which is like a C# reporting... Standardized reporting feature. There are other instances where we've used other languages as well,
but these are definitely the primary ones that we use as part of our stack. - It sounds like you dabble
in a little bit of everything. - Yes, a master of nothing;
decent at most, I would say. - Now, I think everybody's wondering
how is the data being used? - Yeah, so as I said before, my job is to make everyone's
lives easier, more efficient. So like, if I can use the data to automate tasks for our
coaches or scouts, for example.
You know, I'm gonna write
scripts, build projects out that are gonna allow us to do that. You know, building
reports that we're giving to coaches, scouts,
sports performance staff, anyone in the organization
who's making decisions.
If we can help them make those decisions with better information, that's my primary function. And, you know, if we think that is through a model in one instance
or a script in another,
or, you know, a visualization, then that's what we'll
do based on situation. For most projects, I'll
communicate the results to my supervisor, but, you know, we build out everything
for all types of users
in the organization. And then most of those results are kind of disseminated through him. - So what would you say is
the favorite part of your job? - Yeah, for me, it's gotta be the season.
It goes by so fast, but it's obviously like
the reason we're all there, and it's fun to be a part
of the weekly process. You know, it's really all hands on deck getting our staff whatever
they need to be successful.
You know, like I said,
making their lives easier and getting the information
to them quicker. Like, that's where we believe that we can have an advantage, and to see it come into
fruition on game days,
especially on winning game days, it really is a blast. - Yeah, especially this season, right? - It was a fun season. Yeah, it was...
I enjoyed it a lot. We're hoping to have another
one similar to it soon. - Go Bills! So I wanted to talk to you a little bit about your career path.
You received your bachelor's
degree from Clemson University in computer information systems. So how would you say that that background has affected your career path? - Yeah, I mean, my time at Clemson
is a huge reason for why I'm here today. First, it's a great school,
and I loved going there. And then in terms of its
effect on my career path, you know, it did two
main things, I would say. Number one is CIS, computer
gave me a solid technical background. It's primarily computer science with a little bit of business
infused in there as well. That I can take, you know, with me, regardless of industry.
Sports is just what I love to do and what I was fortunate enough to do. But number two, is it... Clemson, you know,
allowed me to spend time working within sports teams
and helped me to realize
that, hey, this is what I
wanted to do as a career, but also that I could do this as a career. Like, you don't even sometimes know that when you first enter college. I'll give a shout out to Alex Bina,
who's the director of applied
science for Clemson football. You know, he gave me my
chance to work with football, get exposure to that whole scene and working with sports data, working with coaches,
networking in the industry.
And he really pushed me
to search in the NFL, which is, you know,
where I was able to land. - It sounds like you've
had the perfect marriage of your your background
in computer science with something that you really
loved to create your career.
So that's awesome. - Yeah. I mean, for me,
that was a huge part... That was a huge draw for computer science. Like, at the beginning
of my program at Clemson, like, I was sort of struggling
with finding out, you know,
"Is this even what I wanna do?" And when I realized I
could really use that for any industry... And then being able to
pair that with sports, like, that's where things
sort of really took off.
- Well, I'm glad that
you found a career path that was really interesting to you. So if somebody else was interested in finding a job like yours, would you recommend they
take the same career path?
What changes would you have made to yours? And what education or
training would you recommend that they complete? - Yeah, I mean, for the same
exact job that I perform, I would recommend getting a
degree in computer science.
You learn so many valuable
ideas and techniques for when you're an analyst, and can really hone
that technical skillset. You know, how do I think in a new way? And in terms of football, you know,
acquiring books, gathering data, trying to do projects on your own... Just show interest and show that you're
willing to learn new things. I didn't play football in high school,
but, you know, I'm trying
every day to, you know, know more than I did the day before. And that's how you get better. For me, I would recommend studying modeling techniques and theory.
I didn't get as much of
that with my program, but it's also important to, you know, apply sound statistical principles and then knowing how to
implement your ideas. And I think that's where computer science
really allowed me to have a
good grasp in these areas. - So are there any hard or
soft skills that you needed in your career that you didn't necessarily realize were important
when you were a student? - Yeah, so in terms of technically,
with my background being computer science, there were some units that
were focused on set-based math, but for the most part, I was programmed to think programmatically and to do things sequentially.
And while there are some scripts that I... You know, I currently write that, you know, will require loops and functions and those types of things, a lot of the time I need
to think of everything
as a set operation. How can I do this with a
single statement of code? And so that was really the
biggest hurdle, at first, in terms of changing my
mindset from, you know, sequential operations to set-based math.
Another thing I would recommend is, like, with SQL, a lot of people get
exposure to SQL in college because, like, it's still used pretty much in most business today, but a lot of it is just
like the basics, right,
of like select star from where. So being able to kind of
go beyond that a little bit and create other types of files that aren't just simple queries, I would definitely recommend
in terms of the technical side.
And then for soft skills, I mean, just emphasizing how
important relationships are, especially in the football industry is, so you gotta be able
to connect with people and, you know, build up your network.
- I think that that's
something that's been coming up in a lot of our interviews
is people are talking about how important it
is to make connections, and that's how that they were
able to grow their career or even find the job that they have now.
- Yeah, absolutely. It's definitely important. - I thought that was
an excellent response. So what made you first interested
in working in your field? - Yeah, I mean, I've loved
sports throughout my life.
I think sports teaches valuable lessons, and when used correctly,
it has a powerful impact. I played basketball and
golf and always enjoyed, you know, analyzing my
play or the play of others. And it really wasn't
until, like I said earlier,
midway through college where I realized that I could do this as a career. - Could you maybe tell us a
little bit about that journey? Like how did you figure out that this was something you could actually
use your analytical skills on, and not something that was just for fun? - Yeah, so right before my sophomore year, I received an email from Alex, who was sending out, like, an all-call
to students of certain majors that they had some data with
the Clemson football team, and they were interested in analyzing it through their Catapult system, which is a player tracking
system that they used.
And I was like, I mean, "Yeah, working with data
and working in sports, like, sounds exactly
like what I wanna do." So I applied for the team, and then I ended up working
with them for three seasons,
basically for the rest
of my college career. And then I was kind of pulled
over to baseball for... I did that for a season as well with them. And so that definitely gave
me a foundation of like, "Okay, I don't know if I can actually
make this happen for my career, but if something ever presents itself, like, I'm gonna jump at it." - Excellent, that's so
great that you were able to find something you're
really interested in.
So I'm sure that, especially
during the season, you are incredibly busy, and it sounds like you're getting requests from all different areas in the Bills. So are you still able to set aside time
for professional development, and if you are, what kind
of activities do you do? - Yeah, definitely more
so in the off season. Even times like now, mainly just trying to acquire new skills,
whether it's, you know, being more comfortable with a
language that I already know or a certain product or learning
something new altogether. I just, you know, find something
that I'm interested in, usually it's sports, and
do a project in that area.
Like, even with football, just, like, trying to find time to read books to fill the gaps in my own education. I really, even in the
last couple of weeks, I've realized like how much I did miss
that portion of school is
just having time to sit down and appreciate learning a new topic. A lot of times when you get to the end of undergrad or whatever, like, you're so ready to be done then,
and I've really kind of found
a new found appreciation for that recently. - That's definitely true. It can be hard to find time
to learn those new things that you're interested in.
You mentioned doing projects. Is that the best way you've
found to kind of practice those new techniques or
get better at languages? Doing a project, whatever it is? - Yeah. I mean, designing it end to end...
Even like, if you're in
software development, like, just coming up with an
idea for a web application, and then just doing it, things like that, because, like, there's
gonna be so many errors and so many things that
you have to overcome
that every step of the way is just... You're learning something
new about that skill. - So was there something you
wish someone had told you before you started your
first professional position in data science?
- Yeah, I would say don't be overwhelmed by how many different types of models or algorithms are out there. You know, on a project by
project basis, do your research. And if you think you're gonna have
to implement something new, then just take the time
to study it and, you know, make sure you meet all the assumptions. You know, you can look up resources online on how to implement it.
I think it's just daunting when you think about, like,
how much is out there. What is it someone said once? Like, "The more we know the less we... The less we understand,"
or something like that.
So don't get overwhelmed, but just take it one project at a time. And, you know, additionally, attention to detail is everything. The amount of validation
that goes into what we do
is so much. You know, it has to be correct, particularly in this industry. So yeah, just making sure
that you've paid attention to every detail and
worked as hard as you can
to make sure that you're
validating your work. - So finally, before we let you go, is there anything else that you would like our listeners to know that
we didn't cover today? - Yeah, I mean, I would
just say, you know,
for those who are listening and might be part of
the Buffalo community, you know, I just want you
to know how thankful I am to be here, to be a part of this. I'm a very, very, very small piece
of hopefully bringing some success to the team and the fan base, so... And yeah, I just wanna encourage students to just take chances and bet on yourself. You know, when I first
got here, I had nothing.
I had, like, 800 bucks to my name. I came up here in my car after graduation, and someone let me sleep on their floor. Like, all I was promised
was an opportunity. I was just betting on myself,
and I'd like to think I've
made the most of that so far, but there's a lot more
work to be done, so... - Well, Shuler, thank you so
much for joining us today. - Yeah, thank you, Heather. It has been a pleasure.
- And to all of our listeners,
if you haven't already, check out our previous podcasts. They're available wherever
you listen to podcasts. - For more information
about starting your career as a data scientist,
go to dataanalytics.buffalostate.edu. Don't forget to subscribe so
that you can get notifications each time we release a new episode of "Buffalo State Data Talk."
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