SkillRating.jl
SkillRating.elo_expected
SkillRating.elo_rating
SkillRating.glicko1_to_glicko2
SkillRating.glicko2
SkillRating.glicko_RD
SkillRating.glicko_RD_increase
SkillRating.glicko_c
SkillRating.glicko_expected
SkillRating.glicko_rating
SkillRating.elo_expected
— Methodelo_expected(RA, RB)
Arguments:
RA
: Rating of player ARB
: Rating of player B
Calculate the expected outcome using elo. See: https://en.wikipedia.org/wiki/Eloratingsystem#Mathematical_details
SkillRating.elo_rating
— Methodelo_rating(r, rjs::Vector, sjs::Vector; k = 32)
Arguments:
r
: Rating of playerrjs
: Ratings of oppenents within rating period.sjs
: Game outcomes from the perspective of the "player": 1 - won, 0.5 - draw, 0 - lost.
Calculate the elo rating change. See: https://en.wikipedia.org/wiki/Eloratingsystem#Mathematical_details
SkillRating.glicko2
— Methodglicko2(μ::Real, ϕ::Real, σ::Real, μjs::Vector{Real}, ϕjs::Vector{Real}, sjs::Vector{Real}; τ=0.05, ϵ=10^-6)
Arguments:
μ
: Rating of playerϕ
: Rating deviation of playerσ
: Rating volatilityμjs
: Ratings of oppenents within rating periodμjs
: Rating deviations within rating periodsjs
: Game outcomes from the perspective of the "player": 1 - won, 0.5 - draw, 0 - lost.τ=0.5
: smaller values constrain the change in volatility over time, reasonable range between 0.3 and 1.2ϵ=10^-6
: Convergence bound
Returns tuple (μ, ϕ, σ)
: glicko2 rating, rating deviation and rating volatility for games in one rating period.
See: http://www.glicko.net/glicko/glicko2.pdf and Glickman, Mark E., "Dynamic paired comparison models with stochastic variances" (2001), Journal of Applied Statistics, 28, 673-689. (http://www.glicko.net/research/dpcmsv.pdf)
SkillRating.glicko_RD
— Methodglicko_RD(r, RD, rjs::Vector, RDjs::Vector, sjs::Vector)
glicko_RD(r, RD, rj::T, RDj::T, sj::T) where T <: Real
Arguments:
r
: Rating of playerRD
: Rating deviation of playerrjs
: Ratings of oppenents within rating period.RDjs
: Rating devations of oppenents within rating period.sjs
: Game outcomes from the perspective of the "player": 1 - won, 0.5 - draw, 0 - lost.
Calculate a new glicko rating deviation for games within a rating period or for a single game.
See: http://www.glicko.net/glicko/glicko.pdf and Glickman, Mark E., "Parameter estimation in large dynamic paired comparison experiments" (1999) Applied Statistics, 48, 377-394 (http://www.glicko.net/research/glicko.pdf)
SkillRating.glicko_RD_increase
— Methodglicko_RD_increase(rd; c = 63.2, maxrd=350)
Arguments:
RD
: Rating deviation at end of rating period.c
: Increase in uncertainty between rating periods.maxRD
: Rating deviation of a player who does not play.
Calculate rating deviation after the end of a rating period.
See: http://www.glicko.net/glicko/glicko.pdf and Glickman, Mark E., "Parameter estimation in large dynamic paired comparison experiments" (1999) Applied Statistics, 48, 377-394 (http://www.glicko.net/research/glicko.pdf)
SkillRating.glicko_c
— Methodglicko_c(rating_perods_to_max, maxrd, medianrd)
Calculate c, the increase in uncertainty between rating periods.
See: http://www.glicko.net/glicko/glicko.pdf and Glickman, Mark E., "Parameter estimation in large dynamic paired comparison experiments" (1999) Applied Statistics, 48, 377-394 (http://www.glicko.net/research/glicko.pdf)
SkillRating.glicko_expected
— Methodelo_expected(RA, RB)
Arguments:
RA
: Rating of player ARB
: Rating of player B
Calculate the expected outcome using glicko.
See: http://www.glicko.net/glicko/glicko.pdf and Glickman, Mark E., "Parameter estimation in large dynamic paired comparison experiments" (1999) Applied Statistics, 48, 377-394 (http://www.glicko.net/research/glicko.pdf)
SkillRating.glicko_rating
— Methodglicko_rating(r, RD, rjs::Vector, RDjs::Vector, sjs::Vector)
glicko_rating(r, RD, rj::T, RDj::T, sj::T) where T <: Real
Arguments:
r
: Rating of playerRD
: Rating deviation of playerrjs
: Ratings of oppenents within rating period.RDjs
: Rating devations of oppenents within rating period.sjs
: Game outcomes from the perspective of the "player": 1 - won, 0.5 - draw, 0 - lost.
Calculate a new glicko rating for games within a rating period or for a single game.
See: http://www.glicko.net/glicko/glicko.pdf and Glickman, Mark E., "Parameter estimation in large dynamic paired comparison experiments" (1999) Applied Statistics, 48, 377-394 (http://www.glicko.net/research/glicko.pdf)
SkillRating.glicko1_to_glicko2
— Methodglicko1_to_glicko2(r::real, RD::Real)
Convert ratings r
and rating deviations RD
from glicko1 (Elo-like) scale to glicko 2 scale (μ and ϕ).