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Let’s talk about F1’s increasing use of
graphical ‘insights’
Currently they’ve got something of a bad
reputation if you look at the prevailing online
discourse - to the point that an AWS insight
onscreen is met with mockery and distrust
- just what AWS wanted, I’m sure.
And the centrepoint of derision is the, frankly
terrible, tyre performance graphic which seems
far more confusing than helpful and often
doesn’t seem to match what we’re seeing
on screen with our own eyeballs. So quite
what ‘insight’ it’s giving us remains
a bit of a mystery.
It was even criticised by Pirelli themselves
for being misleading leading to an apparent
improvement of the algorithm and a clarification
that the graphic shows not ‘tyre wear’
but the output of a whole medley of tyre data
to show you the amount of performance capability
of the tyre already used during the stint.
Which… clarifies nothing?
Essentially it’s trying to tell you how
much lap time the tyre has lost since its
peak but - again - sometimes we’ll watch
cars on ‘red’ tyres catch and pass a car
on ‘green’ tyres so what are we even doing
here?
But are all these new ‘insight’ graphics
bad and should we dismiss algorithmic data
driven graphics during races altogether? Let’s
discuss!
F1 and motorsport in general needs data and
graphics to tell the story much more than
many other sports.
If you look at sports like tennis or baseball
or football you could literally plonk a camera
at a wideshot and view the entire field of
play and almost get away with showing no graphics
at all and you’d still be able to get the
gist of what was happening across the entire
game.
With football, there are few TV graphics to
keep you in the loop - mainly to show the
score, the game time, occasionally player
names and events like substitutions and yellow
cards. That’s all you really need.
And following football - or most ball sports
- involve focusing on one thing - the ball.
This gives you direction of play, which players
from which teams are actively involved and
how close we are to a scoring moment.
Non-sprint motorsports like F1 are very different.
The field of play is miles wide and impossible
to see in a single shot.
There’s no single focal point of action
as there may be battles through the field
between different drivers and teams, different
strategies that play out through different
periods of the race and car performance that
waxes and wanes in different rhythms.
To see the whole picture you need to keep
track of many different things and as such
having information presented to you on screen
about what’s going on right down the field
is important to the audience.
Obviously if you go back a few decades, there
was very limited information on screen and
it was presented infrequently due to technical
limitations and a lot of the narrative work
was done via the commentary team who were
fed a lot more information than we could see,
either via timing screens or through their
fellow journalists in the pitlane.
As time moved forward, more and more live
information was shown on screen directly to
the audience and we needed to know how to
follow it.
Data and graphics can be used well to tell
a story or to allow us to follow several points
of interest at once.
During the final lap of this year’s Austrian
GP, we were following Norris’s battle to
get into a 5 second window behind Hamilton
that would guarantee him a podium due to Lewis’s
looming penalty. When the TV footage cut away
to show the leaders crossing the finish line,
the time gap between Hamilton and Norris stayed
prominently on screen so we could keep track
of the McLaren’s epic push to the podium.
It was a great use of onscreen data to keep
us following the action.
Onscreen information in F1 has often been
raw data - that is, just the facts: a driver’s
laptime, the gaps between cars in seconds
or the actual positions of the cars on the
track.
In the last few years we’ve been getting
more ‘interpreted data’, that is rather
than F1 just showing you data and letting
you figure it out, it’s directly telling
you more about what the data means.
A mild example of this started over a decade
ago when it started colour coding relative
lap and sector times in yellow and green and
purple.
Yellow indicated a time was relatively worse
than a benchmark time, green that it was relatively
better, purple that it was the fastest of
anyone.
In the last couple of years when two cars
are in chase you’ll see not just the gap
between them but yellow and green chevrons
which appear every time the gap is updated
to tell you if it’s growing or closing.
Colour annotations like this let the audience
more quickly understand what’s happening.
You don’t have to spend a moment comparing
times - you immediately know if a car is faster
or slower. This is very useful.
But what we’re seeing now is a big step
further than that.
Let’s take the Pit Strategy Battle graphic
as an example.
This graphic monitors the battle between two
cars that are essentially battling for position
but have been separated on track as one of
the cars has already taken a pitstop. It looks
into the relative pace of both cars, how far
apart they are on track, feeds in the expected
time it takes to make a stop and literally
tells you whether one car will be ahead or
not after the stops.
And this is where we fall into my first bone
of contention with these ‘insights’: don’t
take away the fun of watching a sport.
[NEVER TELL ME THE ODDS]
As an audience, lots of us like keeping an
eye on the laptimes, watching the gap between
the two cars and - knowing roughly the time
lost under a pit stop - have a vague idea
of how close it will be coming out of the
pits. Commentators do this too: ‘I don’t
think he’s doing enough - he’s going to
lose track position at this point’
It can be tense and exciting to watch the
pit stop battle play out - particularly if
on track overtaking is proving difficult.
We want to watch it all unfold, with still
some doubt in our minds over who will come
out on top.
Uncertainty and unpredictability is part of
the joy of watching sport - don’t tell us
what’s going to happen, F1. Give us enough
info to start making connections ourselves
- the gap, the expected pit time, current
pace.
I feel I need to repeat this - do not tell
us what’s going to happen in a live sport.
So this was a rather mild example of interpreted
data - let’s look at full beans algorithmic
data analysis at work then.
An F1 car has hundreds of sensors delivering
live data back to the pitwall constantly.
Across the whole field that amounts to over
a million data points being delivered every
second and AWS has access to much of this
data.
It goes through a defined process of cleaning
the data and running it through several carefully
designed algorithms to deliver what it calls
‘insights’, or easily digestible interpretations
of the data it collects.
This in itself is no bad thing - it happens
all the time in all fields of industry, business,
science and engineering.
We humans can’t read the matrix in real
time - we need it realised for us and that’s
exactly what F1 is trying to do with the absurd
amounts of data it has its hands on during
sessions. And it’s continuing to try and
give us access to that information with six
new Insights rolling out this season.
And I don’t disagree with this in principle
at all - F1’s Director of Data Systems,
Rob Smedley wants to use data to “illustrate
complex scenarios in basic terms” - a mission
this channel can empathise with.
Now, I don’t agree with everything they’re
doing - but let’s start with the good.
Car Performance Scores.
I think these are better than have been given
credit for and the main problem (as with ALL
these algorithmic insights) is the method
behind them is opaque so we don’t readily
know where the numbers are coming from. As
such, we see a car being given a score of
8.7 and go… “o...k…?”
So here, F1 divides up the current track into
different sections: slow speed corners, medium
speed corners, high speed corners and straights.
From here it monitors each car through each
section and works out how it’s performing
in each ‘type’ of section relative to
all the other cars.
So if we say a track has three sections of
high speed corners you can monitor each car’s
pace in each and give them a ranking and a
score relative to a hypothetical best pace.
This data is updated every single lap and
reinterpreted to give you an up-to-date general
idea of how each car is doing in each type
of track characteristic relative to its rivals.
It’s less of a tangible concrete idea than
just raw sector times, but it’s easier to
display and communicate than if you tried
to show all the high speed corner data on
screen. It’s meant to be… well, and insight.
You’re just meant to have an understanding
that, say, Albon is fastest through the high
speed corners in general, but suffering on
the straights or whatever.
So personally I think this is kind of OK as
a touching point for understanding the characteristics
of a car and driver and being able to work
out where cars are gaining and losing time
or where they might be able to work up to
an overtake.
Another Insight is Qualifying and Race Prediction
which… just, no. I feel I’ve already said
my piece on this but leave the predicting
to the fans and pundits. Don’t undercut
your product - unpredictability and suspense
is your biggest selling point!
I feel like I’m going mad here.
And I quickly want to touch on the Driver
Skills Rating and Ultimate Driver Comparison
- both of which make me very uncomfortable.
Driver Skills aims to help identify the best
‘total driver’ on the grid by grinding
lots of performance data into sausages of
rank that will score all the drivers against
each other in an overall comparison.
The Ultimate Driver Comparison aims to compare
modern drivers against classic drivers through
history to determine the fastest of all time.
This is a personal viewpoint, but… In my
opinion, F1 has no place taking an official
stance on this at all. At all.
Fans, pundits, commentators - hey, even the
drivers and teams themselves - can all weigh
in on the great unanswerable question of one
driver versus another but I think it’s really
weird and kind of ‘wrong’ for F1 itself
to outright give an official position on which
driver is better than another.
Like, F1 is just going to publish an official
position that ‘Leclerc is better than Verstappen’
or something? That’s bananas. ‘Having
looked at the data, it is the opinion of Formula
1 that Giovinazzi is the worst driver on the
grid’. Come on. F1 should be absolutely
neutral on this and I don’t think any data
analysis in the world is going to give a satisfying
answer. You’re playing with fire, F1.
And don’t get me started on historical drivers
vs modern ones. That’s one of the great
F1 debates that can never be truly solved
- different eras, cars, rules, philosophies,
technologies. Is F1 really going to have an
official position on Senna vs Schumacher vs
Hamilton. Are they mad? That’s a dangerous
path to tread and I don’t like it at all.
Overall, there’s a complicated line here
that F1 needs to walk carefully.
I agree with the mission - they’ve got a
lot of data and the audience could benefit
from getting more information in a complex
sport. But if the audience has no idea where
this information comes from or what it really
means then they’ll lose trust in it and
continue to mock your so called ‘insights’.
And, to be honest - well presented raw data
interpreted by a good commentary team is 90%
of what you need to enjoy and follow a race
session.
[CREDITS] This is a much more opinionated
piece than usual so I’d love to know your
thoughts. I don’t think AWS insights are
all bad, but def need honing. Would love to
hear positive ideas for what they could do
with all this data for the benefit of the
fans old and new. Let me know! Cheers.
