The Board Game

Heat: Pedal to the Metal is a fast-paced, push-your-luck racing game that captures the thrill and tension of high-speed motorsport with elegant, accessible mechanics. Players manage their car’s momentum using a clever hand-management system, balancing aggressive acceleration against the risk of overheating their engine as they navigate tight corners and long straights. Each race becomes a dynamic tactical puzzle, where timing, drafting behind rivals, and knowing when to take risks can mean the difference between victory and spinning out. With its quick turns, cinematic feel, and just the right level of strategic depth, it delivers an adrenaline-fuelled experience that feels both competitive and effortlessly fun.

The Legends module in Heat: Pedal to the Metal adds automated rival drivers to the race, making the track feel busier and more competitive without needing extra players. Each Legend follows simple but clever rules that keep them fast and unpredictable, forcing you to adapt your strategy as they jostle for position. It’s a great way to scale the game or sharpen your skills, whether playing solo or filling out a full grid.

The generator below is designed to vary difficulty levels and to include additional cars from the various expansion packs.

Legends, Deck Generator

Creating The Deck Generator

One of the limitations of owning the base version of Heat: Pedal to the Metal and additional track expansions, is that you only have access to the original Legends deck. Not only is this deck restricted to the six base game cars, but it’s also relatively small, which limits the randomness and variety in how AI drivers behave. You could approximate this with something simple like rolling a D10+9 and mapping the result to a corner limit, but that approach loses the nuance built into the original deck design.

The official deck encodes several subtle mechanics and limitations:

To recreate and extend this system, I started by analysing the full set of cards. This involved looking at speed distributions per driver, validating how speed correlates with corner limits, and identifying patterns that could be generalised into rules.

From there, I built an initial version of the generator as a C# Azure Function, introducing adjustable difficulty levels:

I then transitioned this into a client-side component for the site. Rather than rewriting it manually, I used an AI assisted workflow with Claude Code, converting the logic from C# into an embeddable React component through a series of iterative prompts. This process included:

The AI handled the bulk of the conversion well, though not everything was seamless, attempts to generate a helmet icon were consistently poor across tools, so I ultimately replaced it with a manually sourced free SVG.

Gaming

Mark Stott

A Solutions Architect and Optimizely MVP at Netcel, creator of the Stott Security and Stott Robots Handler addons for Optimizely CMS. He shares insights and solutions for modern web development challenges.