if you've ever watched hockey you might
think it's a chaotic and unpredictable
game but even the best coaches aren't
always sure if they made a well informed
decision one company is using the power
of AI to help coaches turn seemingly
disorganized gameplay into powerful
analytics with a competitive edge I'm
Arjun duck with NVIDIA and this is I am
AI I was a sports stats geek and I loved
mathematics and I loved the sports so I
thought that there is like a natural
blend between the two and this is what
my life should be all about hockey is
the most complex sport every year it's
getting tougher and tougher to get that
edge so to get that competitive
advantage over other teams especially in
such competitive leagues I realized
there is no automatic data collection
technology in hockey so every team every
league is collecting data manually
probably take it 10 man hours at least
to try and get a big chunk of those
stats
it's just recorded now you've got to
sort them and now you've got to filter
them and everything and just not enough
time before your next game to prepare
you might get everything done and then
the next game started you're missing the
time to actually implement that stuff so
how can a I accelerate this process to
ensure that coaches get the information
they need in time to make a difference
iceberg sports analytics is a platform
that collects information from hockey
games and presents it on a user-friendly
portal that allows you to analyze your
team or player performance
we've developed a hardware system that
has three cameras and each camera is
tracking each zone so we have a
panoramic view of the ice rink the
cameras capture the whole 200-foot
surface of the ice rink attracts each
player 10 times per second what we have
in a raw data set is about a million
data points of player movements referees
movements and also the puck coordinates
after the game you upload it to our
cloud then using artificial intelligence
the game is broken down for you so the
coaches don't have to spend time
breaking down the video themselves
hockey game can be explained by four
basic events its skating pass a shot
attempt and reception reception is just
any pocket touch and we are applying
some machine learning algorithms to
identify those four events when you log
into our system you're gonna see your
basic analytic stats your shots on goal
your total shots your face offs your
possession percentage which is who
possess the more in that game there
are other metrics that are more unique
to iceberg like x qi x ji corresponds to
expected goals and this concept tells
you what's a probability of a specific
shot or any event in the game to be
resulted in a goal
the key lies in their use of a special
class of recurrent neural network that
uses long short term memory or LS TM
units an LS TM unit uses memory from
previous dates as well as current data
to predict the likelihood of a future
event when provided video from a game
the early stages of iceburg system
perform player identification team
composition and calculation of player
and puck trajectories these initial
levels of information allow icebergs LST
m network to generate more insightful
data about the flow of events in a game
iceberg uses this data at deeper levels
of the system to generate an advanced
metrics such as the expected goal
timeline the iceberg system recognizes
complex events such as a zone entry a
power-play or an intercepted past and
interprets how these events affect the
likelihood of a goal being scored
we felt that not all shots are equal so
we've attached the probability metric to
each shot to improve that analysis for
the teams and this way you can identify
which players are actually bringing you
the value from the offensive side of the
game you're only gonna have one leading
scorer and a team that's you know
everyone else you got to figure out what
their strengths is what they're bringing
to the table back in the day you only
had goals and an assist so you didn't
know who got the puck from A to B which
set up that goal but now with the
analytics the guy that doesn't stick out
you you may notice a diamond in the
rough
we rely on coaches feedback a lot we are
trying to build a solution for hockey
coaches by hockey coaches but hockey is
often so complex that coaches can often
disagree on what happened in any given
play how do they feel about another set
of eyes objectively evaluating every
move of each player as a coach I think
good coaches you're you're constantly
learning and and if you have a
technology is powerful this and it
doesn't change the way you look at
things I think you're missing more than
half the battle it's nice to have the
data and the video and the information
to get the guys ready to go the next day
whether you know whatever backs you up
great and what you thought right away
but either way you want to know as a
coach if you were right or if you're
wrong and how to correct it
I wondered how is iceberg able to
deliver analytics in a time frame that
teams can actually use we had been using
CPUs in production but it took us more
than 15 hours to produce one game
and we realized that we had to switch to
GPUs to decrease the production time
because our clients needed the data
faster part of the reason why we
switched to GPUs is we had to cut the
production costs we've cut our costs
more than twice and also the production
time right now is only five hours which
is a significant improvement
I see iceberg evolving into other sports
the first thought is soccer another
sport that I think it'll delve into
really quickly is lacrosse right now
that I don't believe there's any
analytic stats and lacrosse our
technology and the product is easily
scalable because it's fully automated so
for us it doesn't matter if it's 50
clients or 10,000 clients we just need
to rent more computing power to produce
the games and that's the beauty of
computer vision and automation
[Applause]