Nongshim Cup simulation

nongshimcup.jl

using Revise
includet("utils.jl")

function remove_player!(team)
    if length(team) == 1
        team.players = []
    else
        team.players = team.players[2:end]
    end
    team
end

function get_player(team)
    team.players[1]
end

function win_and_continue!(teams; bye = length(teams), verbose=false)
    if length(teams) == 1
        return teams[1]
    end

    if length(teams) == 2
        teams_to_play = [1,2]
    else
        teams_to_play = setdiff(1:length(teams), bye)
    end
    player1 = get_player(teams[teams_to_play[1]])
    player2 = get_player(teams[teams_to_play[2]])

    if verbose
        print("$(player1.name) vs $(player2.name)")
    end

    win_rate = player1_predicted_win_pct(player1, player2)

    if verbose
        print(": $(round(win_rate*100))% ")
    end

    if rand() < win_rate
        if verbose
            println(": $(player1.name) wins")
        end
        remove_player!(teams[teams_to_play[2]])
        bye = teams_to_play[2]
    else
        if verbose
            println(": $(player2.name) wins")
        end
        remove_player!(teams[teams_to_play[1]])
        bye = teams_to_play[1]
    end

    # remove dead teams
    if any(length.(teams) .== 0)
        bye = -1
        teams = teams[length.(teams) .!= 0]
    end

    # println("")
    # for team in teams
    #     println(team)
    # end
    # println("")

    win_and_continue!(teams; bye=bye, verbose=verbose)
end


# simulation 1
china = Team("China", [Player("Yang Dingxin", 3598), Player("Ke Jie", 3709)])
korea = Team("Korea", [Player("Shin Jinseo", 3808), Player("Park Junghwan", 3674)])
japan = Team("Japan", [Player("Iyama Yuta", 3519), Player("Ichiriki Ryo", 3574)])
teams = [korea, japan, china]


win_and_continue!(deepcopy(teams))
@time team_win = [win_and_continue!(deepcopy(teams)) for _ in 1:100_000];
team_won = [team.name for team in team_win];

using StatsBase
countmap(team_won)
team_won2 = [(team.name, length(team)) for team in team_win]
countmap(team_won2)

# simulation 2 - In the unlikely event that Shin Jin Seo loses
china = Team("China", [Player("Yang Dingxin", 3598), Player("Ke Jie", 3709)])
korea = Team("Korea", [Player("Park Junghwan", 3674)])
japan = Team("Japan", [Player("Iyama Yuta", 3519), Player("Ichiriki Ryo", 3574)])
teams = [korea, japan, china]


win_and_continue!(deepcopy(teams), bye=1, verbose=true)
@time team_win = [win_and_continue!(deepcopy(teams)) for _ in 1:100_000];
team_won = [team.name for team in team_win];
using StatsBase
countmap(team_won)
team_won2 = [(team.name, length(team)) for team in team_win];
countmap(team_won2)

# simulation 3 in the likely event that SJS beats ichiriki
china = Team("China", [Player("Yang Dingxin", 3598), Player("Ke Jie", 3709)])
korea = Team("Korea", [Player("Shin Jinseo", 3808), Player("Park Junghwan", 3674)])
japan = Team("Japan", [Player("Ichiriki Ryo", 3574)])
teams = [korea, japan, china]


win_and_continue!(deepcopy(teams), bye=2, verbose=true)
@time team_win = [win_and_continue!(deepcopy(teams)) for _ in 1:100_000];
team_won = [team.name for team in team_win];

using StatsBase
countmap(team_won)
team_won2 = [(team.name, length(team)) for team in team_win];
countmap(team_won2)

using GraphRecipes
using Plots
using LightGraphs
pyplot()

# You had WheelGraph here, but I don't think that is what you intended?
g = DiGraph(3)
add_edge!(g, 1, 2)
add_edge!(g, 1, 3)

names = ["TWX", "SJS", "KJ"]
edgelabels = Dict((1,2)=>"SJS Win", (2,3)=>"KJ Win")
x = [0, 0, 1]
y = [1, 2, 2]
graphplot(g, x=x, y=y, curvature_scalar=0.0, nodesize=0.5,
          node_weights=[0.5,0.5,0.5],
          names=names, nodecolor=:lightgray, color=:black,
          nodeshape=:rect, self_edge_size=0.0,
          edgelabel = edgelabels)

utils.jl

struct Player
    name::String
    rating::Int
end


struct Match
    best_of::Int
end

mutable struct Team
    name::String
    players::Vector{Player}
end

import Base: length

length(t::Team) = length(t.players)

function player1_predicted_win_pct(player1, player2)
    power = (player2.rating-player1.rating)/400
    denom = 1 + 10^power

    1/denom
end

function simulate_match(player1, player2, match)
    p1_win_pct = player1_predicted_win_pct(player1, player2)
    # println(p1_win_pct)

    sum(rand(match.best_of) .< p1_win_pct) > match.best_of/2 ? player1 : player2
end

function player1_predicted_win_pct(player1, player2)
    power = (player2.rating-player1.rating)/400
    denom = 1 + 10^power

    1/denom
end

function play1(player1, player2)
    simulate_match(player1, player2, Match(1))
end

function simulate_match(player1, player2, match)
    p1_win_pct = player1_predicted_win_pct(player1, player2)
    # println(p1_win_pct)

    sum(rand(match.best_of) .< p1_win_pct) > match.best_of/2 ? player1 : player2
end