Written by Antoine Mayerowitz
In Mario Kart 8, choosing your driver, kart’s body, tires, and glider isn’t just
about style — it’s as crucial as your racing skills to win a race. Ever
wondered how to truly find the best ones?
For each of those four elements, you have tens of options. For each option,
there are distinct statistics (speed, acceleration, …) affecting your
performance.
This adds up to an unbelievable amount of builds to choose from.
Hopefully, many choices are just stylistic — they have identical
statistics — but even after ignoring those duplicates, it remains a tough
job to navigate the thousands of options.
Is there any chance to find the best build or is it
just luck? Should you favor speed to be the fastest, or
acceleration
to quickly recover after taking a hit? Let me show you a solution proposed over a
century ago by economist Vilfredo Pareto.
Finding the fastest driver is as simple as ranking them by their speed
statistic. Here you might think that
Bowser or
Wario are a no-brainer.
But you can’t just rely on
speed
to find the optimal build. You have to consider
one as well. Now, finding the best
driverbodytireglider
is not trivial anymore — you have to make trade-offs between
speedaccelerationhandlingweightoffroadmini turbo
and
speedaccelerationhandlingweightoffroadmini turbo Reset
Look closely though! You’ll find out that some options are always dominated. Let’s focus on this poor
Koopa for instance.
Cat Peach has more speed for the same acceleration, and
Toadette has more acceleration for the same speed. Between you and me, if you
want to win, never allow
Koopa to sit in your kart!
You can identify all efficient drivers that, unlike Koopa, are never dominated
on both speed and acceleration. Together, they form what is called
the Pareto front (or frontier).
Mind you: not all elements of the frontier are equally good. You probably won’t
pick a driver sitting on the edge of the frontier because you want some balance
between speed and acceleration. The Pareto efficiency is an
objective criteria to filter out suboptimal choices, but you still need to make up
your final decision.
Given your play style and skills, you may put more
weight on one statistic over
the other. Those preferences will reveal the component on the frontier that
suits you the best.
speedaccelerationhandlingweightoffroadmini turbo
speedaccelerationhandlingweightoffroadmini turbo Best
driverbodytireglider
: {}
speedaccelerationhandlingweightoffroadmini turbo
speedaccelerationhandlingweightoffroadmini turbo
Best
driverbodytireglider
: {}
In practice, you not only choose a driver, but a full set of body, wheels, and glider.
In the next section, I’ll display every build as a distinct point. It will however make
the number of choices explode. But Pareto’s with us!
We’ve had a bit of fun here, but don’t you see the pattern? We’re often faced with
similar trade-offs. You want a meal that’s both cheap and delicious? A job that’s both well-paid, easy, and fulfilling?
A portfolio with low risks and high returns? A flexible and strong material that’s also easy to produce?
A fair taxation that remains efficient
?
A high quality LLM that is also fast and cost-efficient. In all these cases, you’re facing a multi-objective optimization problem, and you
have to make trade-offs.
Of course, if you already know the exact weights you want to assign to each dimension
(i.e., you know your utility function), you reduce the problem to a single objective
optimization. This is because you can combine the dimensions with the weights into a
single quantity to optimize (often called utility, cost, or fitness). In that case, you
don’t need Pareto at all.
But you’re often faced with situations where your utility function is unknown or
uncertain. In those situations, the Pareto front helps you eliminate objectively all the
sub-optimal options. It won’t reveal the one best option right from the outset, but you
may now experiment with these efficient options and select the one that fits you the
best.
I’ve made some simplifying assumptions in this article to keep it readable for a large
audience. In truth, the statistics that I presented are translated into derived in-game
stats that are not always linear with the base statistics. Additionally, there are 4
speed stats and 4 handling stats for all gears (except for the driver), but I decided to
simply average those. I’ve also completely hidden the functional form of the utility
function, which can play a great role. To get access to more details behind this article
or if you just like my work and want to see more in the future, please consider
donating some coins.
Super Mario Wiki
Mario Kart 8 Deluxe in-game statistics
Henry H.
Mario Kart and the Pareto Frontier, 2015