[R-sig-ME] Modelling football matches

[Ben Bolker]

    For a positive-valued variable like distance you might want to 
consider a log-linear model (lmer(log(distance) ~ ...) or a Gamma GLMM 
(glmer(distance  ~ ..., family = Gamma(link="log"))

   I believe the full model here would use random slopes ('slopes' in 
the broad sense since stage is a categorical variable) of stage 
(stage|player) - (stage|game) won't work because each game is only one 
stage.

   I'm not sure about the definition of 'game_part', but you might want 
to add a *fixed* effect of game_part as well as the 'game_part within 
game' nested random effect.

   There's probably a huge amount of covariate information you could add 
(e.g. player's position, player's age), probably other stuff too (random 
effect of team?)

On 2022-12-15 10:17 a.m., Jorge Teixeira wrote:
> Hi.
> 
> 1) Assuming that most are somewhat familiar with football, and that it is
> world cup time, what do you think of this model to compare differences in
> distance covered between stages (group stage vs final stage)?
> 
> lmer(distance ~ stage + (1|player) + (1|game/game_part), data=my_data)
> 
> 2) In theory, which random slopes do you think should be added, if any?
> 
> Thank you.
> 
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> 
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-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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