King Artur

King Artur — CS2 Stats

FI76561199103068946[U:1:1142803218]Steam profile ↗✓ No bans

477Tracked matches61%Win rate2021Tracked since
774Hours in CS1Hrs last 2 wks
CSDB Rating6.0 SolidPositional Player
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 17,529 -444 22 Dec – 4 Jun · 15 days played
17,50019,863peak 19,86322 Dec4 Jun
19,863Peak Premier in tracked matches
59Days played since 2023-12-22

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=14,247), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 4 medianLevel 5 medianvs Level 5
Headshot rate44.5%42.7%43.7%meets
Shot accuracy17.7%11.3%12.0%above
Kill/death ratio0.830.991.020.19 short
Match win rate44.3%43.9%44.7%meets

This profile matches the typical Level 5 player on 3 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGKing ArturFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim82
Positioning46
Utility29

0–100 skill scores via Leetify.

Recent form

HOT49–45–6Last 10049%Win rateLWWLWWLWWW

Last 10 vs previous 10: +30pp win rate · −0.01 avg rating · +6.3pp headshot accuracy · −64ms reaction

Win rate up 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 36%
  • Avg reaction 633ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 33%
  • Avg reaction 614ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 29%
  • Avg reaction 646ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.9 against its own average).

Aim8.2
Utility2.9
Positioning4.6
Opening Duels2.1
Clutch1.0

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

ropz

Plays most like ropz 89% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower positioning profile; lower utility contribution.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.1° off target when enemies appear — placement, not flicking, is the bigger win available.

Positioning. Positioning trails aim by 36 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 673ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim8.2
Positioning4.6
Utility2.9
Mechanics8.2
Opening Duels1.3
Win Impact8.6

Composite 6.0/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02+0.01
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time675ms+8ms
first ⅓ avg 667ms → last ⅓ avg 675ms
Headshot accuracy28.1%+0.0%
first ⅓ avg 28.1% → last ⅓ avg 28.1%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.10Best match rating · 13–6 · train, 14 Mar →
57%Best headshot accuracy · 13–7 · train, 29 Jan →
398msFastest reaction time · 4–13 · nuke, 22 Dec →
13–3Biggest win · boulder, 20 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
8–9In matches decided by ≤2 rounds
10Overtime games

Map breakdown

nukeBest map · 86% over 7infernoWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
mirageC2712–1544%-0.02
ancientC176–1135%-0.02
vertigoC94–544%-0.06
dust2B84–450%-0.02
anubisC73–443%-0.03
cacheS75–271%-0.02
nukeS76–186%-0.03
infernoD62–433%0.00
overpassA53–260%-0.02
trainA53–260%0.01
boulder—11–0100%0.02
grail—10–10%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

21,054Lifetime kills
0.83K/D
1,293Matches
44.3%Match win rate · Top 50% of Level 4 players
44.5%Headshot % · Top 50% of Level 4 players
17.7%Shot accuracy · Top 25% of Level 4 players
3,407MVPs
513Hours (in match)
671Bombs planted
425Bombs defused

Most-used weapons

Lifetime map wins

1,755vertigo
1,431inferno
1,236dust2
1,172nuke
858train
230cbble
76lake
19safehouse

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

54Matches
52%Win rate
0.92Avg K/D
46.9ADR
39%Headshot %

Clutches & streaks

25%1v1 clutch win
0%1v2 clutch win
6Longest win streak

Recent Faceit resultsWWWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage333%0.7514.3
Ancient2100%0.6412.0
Train1100%0.194.0
Dust210%0.6511.0
Nuke10%0.315.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

26.4%Headshot accuracy
36.9%Accuracy (enemy spotted)
42.7%Spray accuracy
86.9%Counter-strafing
10.1°Preaim
673msReaction time
33.3%T opening success
37.4%CT opening success
0.42Enemies flashed / flash
2.9%Flash assists
4.81HE damage / grenade
6.99Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4236 — below the 0.5 mark we flag

    Grenade Lineups →
  2. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 33.2805% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust23–13-0.0943%25 Sept →
inferno16–120.0031%20 Sept →
dust213–110.0232%20 Sept →
anubis4–13-0.0642%20 Sept →
boulder13–30.0231%20 Sept →
cache16–13-0.0129%18 Sept →
dust21–13-0.0831%18 Sept →
mirage13–5-0.0519%5 Sept →
ancient13–11-0.0133%5 Sept →
cache13–3-0.0336%31 Aug →
ancient8–130.0530%31 Aug →
cache8–13-0.0821%23 Aug →
anubis13–10-0.0610%23 Aug →
cache13–40.0518%18 Aug →
ancient6–13-0.0329%22 Jun →
mirage8–13-0.0030%22 Jun →
vertigo7–9-0.1153%22 Jun →
overpass13–70.0326%17 May →
mirage9–13-0.0421%17 May →
inferno13–11-0.0124%17 May →
cache13–6-0.0318%9 May →
cache13–9-0.0619%9 May →
cache3–130.0344%9 May →
ancient15–15-0.0714%27 Mar →
mirage13–11-0.0117%14 Mar →
ancient13–9-0.0020%14 Mar →
inferno5–13-0.0128%7 Mar →
train12–12-0.0531%30 Dec →
anubis13–110.0029%30 Dec →
nuke13–10-0.0024%1 Nov →
anubis10–130.0429%3 Oct →
overpass12–120.0026%26 Sept →
overpass13–5-0.0240%26 Sept →
ancient15–15-0.0227%24 Aug →
inferno8–130.0029%24 Aug →
anubis13–100.0131%22 Aug →
ancient13–16-0.0336%16 Aug →
nuke13–7-0.0933%27 Jul →
overpass13–11-0.0329%27 Jul →
ancient10–13-0.0824%26 Jul →
dust215–15-0.0441%4 Jun →
anubis4–13-0.047%23 May →
nuke13–8-0.0717%23 May →
dust210–13-0.0314%22 May →
mirage4–13-0.0318%22 May →
ancient13–7-0.0213%22 May →
grail6–13-0.0450%9 May →
mirage13–80.0522%7 May →
nuke13–60.0120%7 May →
ancient13–6-0.0320%3 May →
mirage8–13-0.0614%3 May →
mirage11–13-0.0427%17 Apr →
mirage6–130.0626%10 Apr →
mirage9–13-0.0310%26 Mar →
inferno12–120.0437%22 Mar →
mirage6–13-0.0231%22 Mar →
vertigo13–11-0.0723%21 Mar →
train10–13-0.0516%21 Mar →
mirage13–100.0024%18 Mar →
dust213–10-0.0031%14 Mar →
train13–60.1019%14 Mar →
train13–30.0850%14 Mar →
ancient11–13-0.0421%14 Mar →
ancient14–16-0.0415%11 Feb →
vertigo13–9-0.0622%4 Feb →
ancient5–13-0.0521%4 Feb →
ancient7–13-0.1012%3 Feb →
train13–7-0.0357%29 Jan →
nuke9–00.0140%12 Oct →
mirage11–13-0.0340%25 Aug →
inferno11–13-0.0236%31 May →
vertigo6–13-0.0723%31 May →
ancient13–10-0.0128%24 May →
dust213–50.0746%24 May →
vertigo6–13-0.0636%24 May →
vertigo13–11-0.1118%8 Apr →
mirage16–120.0029%8 Apr →
mirage11–13-0.0619%16 Mar →
mirage10–13-0.0240%1 Mar →
mirage13–10-0.0329%13 Feb →
mirage8–13-0.0433%8 Feb →
mirage13–6-0.0423%7 Feb →
anubis6–13-0.1230%7 Feb →
nuke13–70.0439%7 Feb →
mirage13–90.0231%6 Feb →
vertigo13–9-0.0430%6 Feb →
mirage14–16-0.0533%3 Feb →
mirage16–12-0.0036%26 Jan →
ancient8–130.1027%23 Jan →
mirage13–6-0.0010%22 Jan →
overpass8–13-0.0918%21 Jan →
mirage13–10-0.0020%21 Jan →
vertigo11–13-0.0527%8 Jan →
dust213–4-0.0118%26 Dec →
mirage4–13-0.050%23 Dec →
mirage6–130.0220%23 Dec →
nuke4–13-0.1033%22 Dec →
ancient13–80.0227%22 Dec →
vertigo9–13-0.0024%22 Dec →
mirage13–4-0.047%22 Dec →

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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