I have been busy cleaning up the codebase and fixing tons of little issues. Here are main updates:
I have added stats for updates since 6.0 to the site. Please note that while certain graphs like WR vs. Battles played - update 6.0 show big differences between 6.0 and 6.9, the changes in the underlying game statistics are likely less, but are caused just BlitzAnalysiz colleting data more players and especially more new/less active players.
Now the code is much more manageable weith new graph templates. Previously each graph was a copy-paste from the previous similar one (and with little changes along the line) making it hard to manage the code as I discovered issues and fixed bugs. I can now add a new graph (as long as I have a template for the graph type), just with few lines of code like this:
res <- head(stats.update[DT_filter_battles_tank(all.battles, all.battles.new, tier, is_premium), .('Average WR' = mean(WR), 'Player WR' = mean(WR.global), 'Players' = uniqueN(account_id), 'Battles' = sum(all.battles), 'Premium' = first(is_premium)), by=name ][Players >= min_players][ order(-`Average WR`)],n=topN); res <- prep_plot_tank(res,'Average WR') title = get_plot_title_top_tanks('Average WR', topN = 20) plot_col_discrete_2Y(res,title, update, 'Tank', 'Average WR', 'Player WR', fill_var = 'Tank type')
res <- head(stats.update[, .('Avg. WR' = mean(WR), 'Player WR' = mean(WR.global), Players=uniqueN(account_id), Battles = sum(all.battles), Premium= unique(is_premium)), by=name ][Players >= min_players][ order(-`Avg. WR`)],n=topN); setnames(res, 'name', 'Tank'); res[, `Avg. WR`:=`Avg. WR` * 100]; res[, `Player WR`:=`Player WR` * 100]; res[Premium==TRUE, `Tank type`:='Premium'] res[Premium==FALSE, `Tank type`:= 'Researchable'] res[,`Tank type` := as.factor(`Tank type`)] res[,Premium := NULL] setcolorder(res,c('Tank', 'Avg. WR','Player WR', 'Players', 'Battles', 'Tank type')); ggplot(res) + aes(x = reorder(Tank, `Avg. WR`, (function (x) -x)), y = `Avg. WR`, fill= `Tank type`) + geom_col(aes(group=`Tank type`)) + scale_fill_manual('Tank type', values = c('Premium'='black', 'Researchable' = 'grey')) + geom_point(aes(x = reorder(Tank, `Avg. WR`, (function (x) -x)), y=`Player WR`, color = color.2nd_series, shape='Player WR'), shape='-', size=20, inherit.aes = FALSE) + scale_color_identity(name = NULL, guide='legend', labels= 'Player WR') + scale_x_discrete('Tank') + scale_y_continuous('Win rate', labels = div_format(seq(0,100,5),1,'%'), breaks = seq(0, 100, 5)) + theme(panel.background = element_rect(fill = 'white'), plot.title = element_text(hjust = 0.5), panel.grid.minor = element_line(colour="grey", size=0.5), axis.text.x = element_text(angle = 45, hjust = 1), plot.subtitle = element_text(hjust = 1), legend.key = element_blank()) + ggtitle(paste('TOP',topN, 'Tanks by WR'), subtitle = paste("Update", update));
In addition for the graph templates makin me happier, those ensure more consistent look and feel and allow me to easily add new graphs - there is never enough of those, right?
For couple of gprahs I have added unfiltrered (i.e. all players) versions of those. Blitz has huge number of players who just play few games during the whole update. More than 10% of the players play less than e-i-g-h-t (8) battles during an update. And only small share of those players are ever looked at BlitzStars or happen to be recorded into replays sent to WoTinspector.com, therefore never ending up into Blitzanalysiz.com account database. For this reason I filter players based on minimun battle count requirement for many of the graphs. Otherwise the graphs would show players with 100% WR where in fact they had only one (lucky) game during the whole update.