A simple use case

This vignette covers how to use some functions from the CSGo package in a use case format.

Data Extraction and Analysis

The first step to use the CSGo package is to have your own credentials (API key) to pull the CSGo data from the Steam API. For more information about how to get your own API Key run in your R vignette("auth", package = "CSGo").

Now that you already have your API Key you should be able to collect your own CSGo data as well as your friends’ data. I hope my friend Rodrigo doesn’t mind us playing with his data (he is the ‘76561198263364899’)!

First let’s pull his CSGo statistics:

library(CSGo)

# to get the statistics of the user 76561198263364899
rodrigo_stats <- get_stats_user(api_key = 'your_key', user_id = '76561198263364899')

Let’s just filter the obtained data frame by “kills” and “weapon” to create an analysis of kills by type of weapon.

library(dplyr)
library(stringr)

rodrigo_weapon_kill <- rodrigo_stats %>%
  filter(
    str_detect(name, 'kill'),
    type == ' weapon info'
  ) %>%
  arrange(desc(value))

Now let’s take a look at the graphic!

PS: To make the graphic even more beautiful I recommend getting the “Quantico” font from Google fonts using the showtext package!

library(ggplot2)
library(showtext)

## Loading Google fonts (https://fonts.google.com/)
font_add_google("Quantico", "quantico")

rodrigo_weapon_kill %>%
  top_n(n = 10, wt = value) %>%
  ggplot(aes(x = name_match, y = value, fill = name_match)) +
  geom_col() +
  ggtitle("KILLS BY WEAPON") +
  ylab("Number of Kills") +
  xlab("") +
  labs(fill = "Weapon Name") +
  theme_csgo(text = element_text(family = "quantico")) +
  scale_fill_csgo()

kills_weapon

So, these are the top 10 weapons by kills, but.. What about the efficiency? Is the ak47 the Rodrigo’s more efficient weapon? First, let’s define “efficiency”:

kills_efficiency means how many shots he did to kill (ex: 32% shots will kill)
hits_efficiency means how many shots to have a hit, this is more related to Rodrigo’s ability with each weapon (ex: 35% of the shots will hit).
hits_to_kill means how many hits are necessary to kill, this is more related to the weapon power/efficiency (ex: 91% of the hits will kills).


rodrigo_efficiency <- rodrigo_stats %>%
  filter(
    name_match %in% c("ak47", "aug", "awp", "fiveseven",
                      "hkp2000", "m4a1", "mp7", "p90",
                      "sg556", "xm1014")
  ) %>%
  mutate(
    stat_type = case_when(
      str_detect(name, "shots") ~ "shots",
      str_detect(name, "hits") ~ "hits",
      str_detect(name, "kills") ~ "kills"
    )
  ) %>% 
  pivot_wider(
    names_from = stat_type, 
    id_cols = name_match, 
    values_from = value
  ) %>%
  mutate(
    kills_efficiency = kills/shots*100,
    hits_efficiency = hits/shots*100,
    hits_to_kill = kills/hits*100
  )

kbl(rodrigo_efficiency) %>%
  kable_styling()

name_match	kills	shots	hits	kills_efficiency	hits_efficiency	hits_to_kill
fiveseven	1288	28187	5558	4.569482	19.71831	23.17380
xm1014	5611	205982	42541	2.724024	20.65278	13.18963
p90	3469	133273	20245	2.602928	15.19062	17.13510
awp	2051	6260	2235	32.763578	35.70288	91.76734
ak47	6969	154852	24823	4.500426	16.03014	28.07477
aug	2120	37949	8487	5.586445	22.36423	24.97938
hkp2000	1401	36975	6737	3.789047	18.22042	20.79561
sg556	1243	25091	4567	4.953968	18.20175	27.21699
mp7	1788	52657	10186	3.395560	19.34406	17.55350
m4a1	3526	81126	14687	4.346325	18.10394	24.00763

rodrigo_efficiency %>%
  top_n(n = 10, wt = kills) %>%
  ggplot(aes(x = name_match, size = shots)) +
  geom_point(aes(y = kills_efficiency, color = "Kills Efficiency")) +
  geom_point(aes(y = hits_efficiency, color = "Hits Efficiency")) +
  geom_point(aes(y = hits_to_kill, color = "Hits to Kill")) +
  ggtitle("WEAPON EFFICIENCY") +
  ylab("Efficiency (%)") +
  xlab("") +
  labs(color = "Efficiency Type", size = "Shots") +
  theme_csgo(
    text = element_text(family = "quantico"),
    panel.grid.major.x = element_line(size = .1, color = "black",linetype = 2)
  ) +
  scale_color_csgo()

weapon_effic

In conclusion, I would advise Rodrigo to use the awp in his next games, because this weapon presented the best efficiency in terms of shots to kill, shots to hit, and hits to kill. But we definitely need more shots with this weapon to see if this efficiency remains.. hahahaha