cObRa

cObRa — CS2 Stats

LK76561198086794559[U:1:126528831]Steam profile ↗✓ No bans

1,054Tracked matches45%Win rate2020Tracked since
2,805Hours in CS8Hrs last 2 wks
CSDB Rating4.6 DevelopingSupport
Premier CS Rating12,277Blue band · top ~42.8% of ranked players (population est.)
FaceitLevel 3Top 90.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 5 Nov 2026 (10 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 12,277 +1,323 24 May – 5 Nov · 50 days played
9,99915,164peak 15,16424 May5 Nov
15,373Peak Premier in tracked matches
72Days played since 2026-05-24

Premier CS Rating

  • 2,887 below peak (15,164)
  • +1,934 over 30 days · improving
  • -831 over 90 days
  • Next: Purple band at 15,000 — 2,723 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Blue band first seen 2026-10-31
  • Light Blue band first seen 2026-10-31

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 3 among CSDB-tracked players (n=10,677), 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 3 medianLevel 4 medianvs Level 4
Headshot rate38.7%41.8%42.7%4.0% short
Shot accuracy9.0%12.2%11.2%2.2% short
Kill/death ratio0.820.980.990.17 short
Match win rate42.7%43.3%43.9%1.2% short

This profile sits below the typical Level 4 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGcObRaFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER12,277 · Blue bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim46
Positioning50
Utility55

0–100 skill scores via Leetify.

Recent form

STEADY50–49–1Last 10050%Win rateWWWWLLWLLW

Last 10 vs previous 10: +20pp win rate · +0.04 avg rating · −0.9pp headshot accuracy · −8ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 16%
  • Avg reaction 577ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 615ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 15%
  • Avg reaction 619ms

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: Support — Utility contribution stands above the rest of this profile (+1.4 against its own average).

Aim4.6
Utility5.5
Positioning5.0
Opening Duels0.9
Clutch5.0

Strong CT-side openerEffective flashes

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

iM

Plays most like iM 72% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; lower aim profile.

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

Strengths

Flashes. 0.78 enemies blinded per flash — utility that consistently lands.

Areas to improve

Reaction time. 632ms 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

Aim4.6
Positioning5.0
Utility5.5
Mechanics6.9
Opening Duels3.2
Win Impact3.3

Composite 4.6/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01+0.01
first ⅓ avg -0.02 → last ⅓ avg -0.01
Reaction time640ms−24ms
first ⅓ avg 664ms → last ⅓ avg 640ms
Headshot accuracy15.9%+2.7%
first ⅓ avg 13.1% → last ⅓ avg 15.9%

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

0.13Best match rating · 13–8 · inferno, 5 Nov →
30%Best headshot accuracy · 13–8 · nuke, 27 Jul →
422msFastest reaction time · 13–10 · anubis, 20 Oct →
13–1Biggest win · dust2, 31 Jul →

Across the last 100 tracked matches.

Highlights

8Longest win streak
W4Current streak
9–6In matches decided by ≤2 rounds
4Overtime games

Map breakdown

dust2Best map · 67% over 33infernoWeakest map · 29% over 14
MapGradePlayedRecordWin rateAvg rating
dust2S3322–1167%-0.01
mirageB2412–1250%-0.02
infernoD144–1029%-0.04
nukeC114–736%-0.03
anubisA95–456%-0.04
ancientD62–433%0.00
cache—20–20%-0.08
overpass—11–0100%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

55,669Lifetime kills
0.82K/D
3,582Matches
42.7%Match win rate
38.7%Headshot %
9.0%Shot accuracy
6,285MVPs
1,495Hours (in match)
4,398Bombs planted
746Bombs defused

Most-used weapons

Lifetime map wins

24,665dust2
2,964inferno
1,248vertigo
1,041nuke
626train
61cbble
42bank
17office

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

Faceit stats

Combat

63Matches
46%Win rate
0.85Avg K/D
66.3ADR
50%Headshot %

Clutches & streaks

45%1v1 clutch win
12%1v2 clutch win
6Longest win streak

Recent Faceit resultsLWWWL

MapMatchesWin rateAvg K/DAvg kills
Dust21856%0.8812.1
Nuke838%0.608.9
Inferno743%0.589.3
Mirage714%0.9413.7
Vertigo450%0.7818.3
Anubis367%1.0112.0
Ancient333%0.527.7
Train250%1.1416.0

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.

15.6%Headshot accuracy
29.1%Accuracy (enemy spotted)
27.7%Spray accuracy
81.0%Counter-strafing
10.3°Preaim
632msReaction time
41.6%T opening success
44.2%CT opening success
0.78Enemies flashed / flash
4.3%Flash assists
7.54HE damage / grenade
7.02Flashes / match

Recommended for you

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.

29% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–50.0413%14 Nov →
dust213–110.0119%7 Nov →
inferno13–80.1322%5 Nov →
dust213–100.0419%5 Nov →
anubis6–13-0.089%4 Nov →
dust28–13-0.0117%4 Nov →
dust213–9-0.0312%3 Nov →
mirage5–13-0.017%3 Nov →
ancient9–13-0.0013%2 Nov →
dust213–6-0.0514%30 Oct →
cache7–13-0.0915%29 Oct →
nuke8–13-0.0318%26 Oct →
dust213–2-0.0213%24 Oct →
anubis13–10-0.0325%20 Oct →
mirage13–80.0715%19 Oct →
ancient13–60.0923%14 Oct →
dust22–13-0.0712%13 Oct →
anubis9–13-0.0410%11 Oct →
mirage3–13-0.0817%10 Oct →
anubis1–13-0.107%9 Oct →
inferno10–13-0.0325%6 Oct →
mirage12–120.0215%3 Oct →
mirage13–20.0229%2 Oct →
mirage10–130.0015%29 Sept →
dust213–50.0210%29 Sept →
ancient13–20.1023%28 Sept →
nuke5–13-0.0112%28 Sept →
mirage9–13-0.0814%28 Sept →
nuke11–13-0.0511%26 Sept →
ancient2–13-0.0314%26 Sept →
mirage13–11-0.0321%17 Sept →
mirage6–130.0014%14 Sept →
mirage13–100.0021%11 Sept →
mirage4–13-0.074%10 Sept →
inferno11–13-0.0510%28 Aug →
inferno11–13-0.079%27 Aug →
dust28–13-0.0314%23 Aug →
mirage10–130.0322%20 Aug →
dust213–8-0.0619%18 Aug →
nuke13–9-0.0022%13 Aug →
anubis13–5-0.0211%7 Aug →
inferno7–13-0.064%6 Aug →
mirage16–14-0.0621%5 Aug →
dust213–110.0412%5 Aug →
nuke9–13-0.0520%5 Aug →
mirage13–100.017%4 Aug →
dust213–10.0422%31 Jul →
ancient5–13-0.085%29 Jul →
dust213–80.0419%28 Jul →
dust211–130.0315%27 Jul →
nuke13–8-0.0430%27 Jul →
ancient4–13-0.068%26 Jul →
mirage8–13-0.057%26 Jul →
dust210–13-0.0717%17 Jul →
mirage16–140.029%14 Jul →
anubis4–13-0.029%13 Jul →
dust213–10-0.0412%13 Jul →
cache2–13-0.0716%9 Jul →
dust27–13-0.0720%8 Jul →
mirage13–9-0.088%4 Jul →
dust213–50.0315%1 Jul →
mirage11–13-0.0617%30 Jun →
inferno2–13-0.1314%29 Jun →
inferno3–13-0.079%27 Jun →
dust213–9-0.0116%25 Jun →
mirage6–13-0.0111%24 Jun →
overpass13–7-0.0420%24 Jun →
dust23–90.0213%24 Jun →
dust28–13-0.0519%23 Jun →
inferno13–7-0.0420%22 Jun →
dust213–11-0.0027%22 Jun →
dust213–80.0311%21 Jun →
inferno2–13-0.130%18 Jun →
nuke0–5-0.0413%17 Jun →
mirage13–70.048%17 Jun →
nuke1–13-0.120%16 Jun →
dust29–13-0.0411%13 Jun →
inferno11–13-0.058%13 Jun →
anubis13–90.0316%13 Jun →
inferno13–40.0719%13 Jun →
dust213–40.0226%12 Jun →
dust213–100.0113%11 Jun →
inferno6–13-0.0812%11 Jun →
dust213–5-0.0127%10 Jun →
anubis13–8-0.0410%7 Jun →
mirage16–14-0.0314%7 Jun →
nuke13–8-0.0613%6 Jun →
dust213–90.018%6 Jun →
dust213–4-0.0310%5 Jun →
inferno13–11-0.0127%5 Jun →
mirage13–5-0.067%5 Jun →
nuke6–130.0111%2 Jun →
nuke13–40.0815%2 Jun →
dust27–13-0.0219%31 May →
dust28–13-0.046%31 May →
dust213–10-0.0211%30 May →
mirage13–10-0.058%30 May →
inferno4–13-0.0512%26 May →
mirage8–13-0.0716%26 May →
anubis16–14-0.048%24 May →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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