Category: Data Science

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FASERIP-Slugfest: Shang-Chi vs the Six Boxers

I’ll post the rat pack vs the lawyer later – seems you will still be able to get some advice in James Herbert land though.

However, thought this is an interesting scenario – given anyone can hit in FASERIP, and this is just vanilla toe-to-toe, although have now added basic stuns in. Should also perhaps add that a slammed opponent misses a turn, and check that all this works. Added kills as well, so got worse for our rat friend vs the cat, would only prevail in a couple in a thousand.

Have not added in karma yet either, which should help those with more – Shang has enough to change one hit to a miss, anyway.

In my basic spreadsheet of stats had one that is all Typical. Which means a normal human with some training in Fighting, so could call them them a boxer, or something similar. Not programmed in any Talents as yet – martial arts will be first. In the above, Shang would get a column shift to hit and the ability to try for 3 multi-attacks and an initiative bonus. The framework does individual initiative, so that one won’t matter as much – would have to add in a ‘set all initiatives to first roll’ addition later to do group initiative.

Battles: 1000; Sum of rounds: 5980; martialarts: 0.59 ± 0.02; boxer: 0.41 ± 0.02;

Team martialarts = winning battles: 588; perfect battles: 0; close-call battles: 0;
Team boxer = winning battles: 412; perfect battles: 0; close-call battles: 412;
------------------------------------------------- Combattants ------------------------------------------------
Boxer: {team=boxer; avg Health=-8.576 (from 24); damage done (per battle average)= 8.98; hits/slams/stuns/kills/misses (PBA)= 1.5/0.0/0.0/0.0/1.43; rounds (PBA)=3.07;}
Boxer: {team=boxer; avg Health=-8.576 (from 24); damage done (per battle average)= 8.98; hits/slams/stuns/kills/misses (PBA)= 1.5/0.0/0.0/0.0/1.43; rounds (PBA)=3.07;}
Boxer: {team=boxer; avg Health=-8.688 (from 24); damage done (per battle average)= 8.52; hits/slams/stuns/kills/misses (PBA)= 1.42/0.0/0.0/0.0/1.39; rounds (PBA)=2.98;}
Amazing Martial Artist: {team=martialarts; avg Health=17.4 (from 120); damage done (per battle average)= 97.31; hits/slams/stuns/kills/misses (PBA)= 4.07/1.88/0.54/0.0/1.31; rounds (PBA)=5.67;}
Boxer: {team=boxer; avg Health=-8.412 (from 24); damage done (per battle average)= 8.39; hits/slams/stuns/kills/misses (PBA)= 1.4/0.0/0.0/0.0/1.42; rounds (PBA)=2.98;}
Amazing Martial Artist: {team=martialarts; avg Health=17.4 (from 120); damage done (per battle average)= 97.31; hits/slams/stuns/kills/misses (PBA)= 4.07/1.88/0.54/0.0/1.31; rounds (PBA)=5.67;}
Boxer: {team=boxer; avg Health=-8.688 (from 24); damage done (per battle average)= 8.52; hits/slams/stuns/kills/misses (PBA)= 1.42/0.0/0.0/0.0/1.39; rounds (PBA)=2.98;}
Boxer: {team=boxer; avg Health=-8.964 (from 24); damage done (per battle average)= 8.43; hits/slams/stuns/kills/misses (PBA)= 1.4/0.0/0.0/0.0/1.43; rounds (PBA)=3.0;}
Boxer: {team=boxer; avg Health=-8.412 (from 24); damage done (per battle average)= 8.39; hits/slams/stuns/kills/misses (PBA)= 1.4/0.0/0.0/0.0/1.42; rounds (PBA)=2.98;}
Boxer: {team=boxer; avg Health=-8.468 (from 24); damage done (per battle average)= 8.14; hits/slams/stuns/kills/misses (PBA)= 1.36/0.0/0.0/0.0/1.39; rounds (PBA)=2.88;}
Boxer: {team=boxer; avg Health=-7.504 (from 24); damage done (per battle average)= 8.84; hits/slams/stuns/kills/misses (PBA)= 1.47/0.0/0.0/0.0/1.36; rounds (PBA)=2.98;}
Boxer: {team=boxer; avg Health=-8.468 (from 24); damage done (per battle average)= 8.14; hits/slams/stuns/kills/misses (PBA)= 1.36/0.0/0.0/0.0/1.39; rounds (PBA)=2.88;}
Boxer: {team=boxer; avg Health=-7.504 (from 24); damage done (per battle average)= 8.84; hits/slams/stuns/kills/misses (PBA)= 1.47/0.0/0.0/0.0/1.36; rounds (PBA)=2.98;}
Boxer: {team=boxer; avg Health=-8.964 (from 24); damage done (per battle average)= 8.43; hits/slams/stuns/kills/misses (PBA)= 1.4/0.0/0.0/0.0/1.43; rounds (PBA)=3.0;}

Shang-Chi stats currently from here https://classicmarvelforever.com/cast/shang_chi.htm

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FASERIP-Slugfest – rats on the run

Things are tough in ratland when you add in a cat’s killing ability. Maybe we should go James Herbert next and have a rat pack versus a person as a test. Not that those are giant mutant killer rats. Although possible good superhuman testing ground?

Battles: 1101; Sum of rounds: 6336; rodent: 0.0 ± 0.0; feline: 1.01 ± NA; rodent: 0.0 ± 0.0; feline: 1.099 ± NA;
Team rodent = winning battles: 2; perfect battles: 0; close-call battles: 0;
Team feline = winning battles: 1099; perfect battles: 0; close-call battles: 0;
------------------------------------------------- Combattants ------------------------------------------------
Rat: {team=rodent; avg hp=0.005449591280653951 (from 8); avg healing spells left=0.0 (from 0); damage done (per battle average)= 3.6412352406902815; hits/slams/stuns/kills/misses (PBA)= 1.8206176203451407/0.0/0.0/0.0/2.751135331516803; rounds (PBA)=4.572661217075386;}
Cat: {team=feline; avg hp=16.717529518619436 (from 24); avg healing spells left=0.0 (from 0); damage done (per battle average)= 3.997275204359673; hits/slams/stuns/kills/misses (PBA)= 1.9986376021798364/0.0/0.45049954586739327/0.05131698455949137/2.9981834695731155; rounds (PBA)=5.4959128065395095;}
Rat: {team=rodent; avg hp=0.005449591280653951 (from 8); avg healing spells left=0.0 (from 0); damage done (per battle average)= 3.6412352406902815; hits/slams/stuns/kills/misses (PBA)= 1.8206176203451407/0.0/0.0/0.0/2.751135331516803; rounds (PBA)=4.572661217075386;}
Cat: {team=feline; avg hp=16.717529518619436 (from 24); avg healing spells left=0.0 (from 0); damage done (per battle average)= 3.997275204359673; hits/slams/stuns/kills/misses (PBA)= 1.9986376021798364/0.0/0.45049954586739327/0.05131698455949137/2.9981834695731155; rounds (PBA)=5.4959128065395095;}

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FASERIP-Slugfest

I mentioned Matteo Ferla’s DnD-battler yesterday.

https://github.com/bluetyson/FASERIP-Slugfest

I have started adapting this to work with FASERIP. Obviously the mechanics are different, but the basic framework is there, which is why I wanted to use it – all the hard work with creatures, encounters, arenas, running many simulations and tallying them just needs different characteristics and algorithms inserted.

Very much a work in progress, this is like version 0.01.

You can do this, however :-

————————————————————————————————————–
Battles: 100; Sum of rounds: 506; feline: 0.97 ± 0.02; rodent: 0.03 ± 0.02;
> Team feline = winning battles: 97; perfect battles: 0; close-call battles: 0;
> Team rodent = winning battles: 3; perfect battles: 0; close-call battles: 0;
————————————————- Combattants ————————————————
Rat: {team=rodent; avg hp=-0.56 (from 8); avg healing spells left=0.0 (from 0); damage done (per battle average)= 3.31; hits/misses (PBA)= 1.655/2.305; rounds (PBA)=3.975;}
Cat: {team=feline; avg hp=9.38 (from 16); avg healing spells left=0.0 (from 0); damage done (per battle average)= 4.28; hits/misses (PBA)= 1.62/2.595; rounds (PBA)=4.7;}
Rat: {team=rodent; avg hp=-0.56 (from 8); avg healing spells left=0.0 (from 0); damage done (per battle average)= 3.31; hits/misses (PBA)= 1.655/2.305; rounds (PBA)=3.975;}
Cat: {team=feline; avg hp=9.38 (from 16); avg healing spells left=0.0 (from 0); damage done (per battle average)= 4.28; hits/misses (PBA)= 1.62/2.595; rounds (PBA)=4.7;}

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DnDBattler

Matteo Ferla has written a python 5E D&D encounter simulator that I have been meaning to get to for some time. Too many real life models to deal with until now.

https://github.com/matteoferla/DnD-battler

He also has an online version here:- https://dnd.matteoferla.com/

http://squidonius.blogspot.com/

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AI: The Lost Irulan

He is not a philosopher nor a scholar, nor a poet. He is not a warrior nor a lover, nor a man of science. He is a poet of the earth, of the stars, of the cosmos, of the universe, the lord of all the world. He is justness without and justice within.

—’Muad’Dib: The God King of Arrakis’ by the Princess Irulan

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Wilderness Simulator Stats – Python

I took the java version from https://cosmicheroes.space/blog/index.php/2021/12/27/wilderness-simulator-stats/

and converted to python – there’s a jupyter notebook here:-

WildernessEncounterSim – Jupyter Notebook

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