OGKMALIK

OGKMALIK — CS2 Stats

UG76561199220270106[U:1:1260004378]Steam profile ↗✓ No bans

544Tracked matches31%Win rate2024Tracked since
1,179Hours in CS50Hrs last 2 wks
CSDB Rating3.2 LearningSupport
Premier CS Rating2,191Grey band · top ~90.7% of ranked players (population est.)
WingmanSilver Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Nov 2026 (yesterday). 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: 2,191 -987 8 Apr – 13 Nov · 12 days played
1,6683,178peak 3,1788 Apr13 Nov
3,289Peak Premier in tracked matches
32Days played since 2026-04-08

Premier CS Rating

  • 987 below peak (3,178)
  • Next: Light Blue band at 5,000 — 2,809 to go

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate50.6%38.2%39.9%above
Shot accuracy0.0%3.6%7.0%7.0% short
Kill/death ratio0.770.830.920.15 short
Match win rate45.9%40.2%42.3%above

This profile matches the typical Light Blue band player on 2 of 4 comparable metrics.

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

Share this profile

CSDB.GGOGKMALIKPREMIER2,191 · Grey bandcsdb.gg/stats

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Performance scores

Aim42
Positioning28
Utility52

0–100 skill scores via Leetify.

Recent form

COLD40–59–1Last 10040%Win rateLLLLLTLWWL

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · −0.9pp headshot accuracy · −70ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 0–5 · 0% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 11%
  • Avg reaction 628ms

Last 10

  • 2–7–1 · 20% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 15%
  • Avg reaction 626ms

Last 20

  • 5–14–1 · 25% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 16%
  • Avg reaction 661ms

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 (+2.5 against its own average).

Aim4.2
Utility5.2
Positioning2.8
Opening Duels0.0

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

NiKo

Plays most like NiKo 73% 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

Areas to improve

Reaction time. 657ms 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

Aim4.2
Positioning2.8
Utility5.2
Mechanics6.2
Opening Duels0.4
Win Impact0.0

Composite 3.2/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05+0.01
first ⅓ avg -0.05 → last ⅓ avg -0.05
Reaction time647ms−41ms
first ⅓ avg 688ms → last ⅓ avg 647ms
Headshot accuracy16.5%−1.0%
first ⅓ avg 17.6% → last ⅓ avg 16.5%

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

0.11Best match rating · 13–9 · inferno, 29 Oct →
33%Best headshot accuracy · 4–13 · vertigo, 7 Jul →
469msFastest reaction time · 10–13 · ancient, 7 Nov →
13–1Biggest win · anubis, 25 Oct →

Across the last 100 tracked matches.

Highlights

8Longest win streak
L5Current streak
9–4In matches decided by ≤2 rounds
3Overtime games

Map breakdown

anubisBest map · 50% over 6mirageWeakest map · 33% over 24
MapGradePlayedRecordWin rateAvg rating
mirageD248–1633%-0.05
dust2C166–1038%-0.05
infernoB157–847%-0.02
nukeC146–843%-0.03
ancientC145–936%-0.05
cacheD62–433%-0.05
anubisB63–350%-0.04
vertigo—32–167%-0.05
train—11–0100%0.04
overpass—10–10%-0.03

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (33% over 24). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

18,629Lifetime kills
0.77K/D
1,411Matches
45.9%Match win rate · Top 25% of Grey band
50.6%Headshot % · Top 10% of Grey band
0.0%Shot accuracy
2,880MVPs
556Hours (in match)
1,777Bombs planted
238Bombs defused

Most-used weapons

Lifetime map wins

2,695inferno
2,278nuke
1,135dust2
336train
228vertigo
16italy
7lake
2safehouse

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

Skill profile

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

16.2%Headshot accuracy
27.8%Accuracy (enemy spotted)
28.0%Spray accuracy
77.8%Counter-strafing
9.6°Preaim
657msReaction time
33.3%T opening success
29.4%CT opening success
0.47Enemies flashed / flash
3.1%Flash assists
8.63HE damage / grenade
11.80Flashes / 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 0.4731 — 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 33.2773% — below the 40% mark we flag

Spend your practice time on Mirage

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 24 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust23–13-0.1217%13 Nov →
mirage1–13-0.065%13 Nov →
mirage4–13-0.0816%12 Nov →
inferno9–13-0.094%12 Nov →
dust25–13-0.0613%12 Nov →
inferno15–15-0.0423%11 Nov →
dust28–13-0.1021%11 Nov →
nuke13–40.0121%11 Nov →
dust213–8-0.0323%11 Nov →
ancient2–13-0.0411%11 Nov →
cache13–5-0.0212%11 Nov →
nuke8–13-0.1021%11 Nov →
mirage9–13-0.0930%11 Nov →
ancient8–13-0.0718%9 Nov →
cache9–13-0.0714%9 Nov →
anubis11–13-0.0211%9 Nov →
ancient13–8-0.026%8 Nov →
mirage10–13-0.0918%8 Nov →
nuke13–6-0.0219%8 Nov →
mirage6–13-0.0116%8 Nov →
dust27–13-0.0424%8 Nov →
dust213–7-0.0218%8 Nov →
ancient10–13-0.046%7 Nov →
anubis7–13-0.0412%7 Nov →
dust213–4-0.029%7 Nov →
dust23–13-0.0923%7 Nov →
nuke7–13-0.0412%7 Nov →
vertigo13–7-0.0025%1 Nov →
mirage13–80.0323%1 Nov →
nuke4–13-0.0211%1 Nov →
cache7–13-0.0413%1 Nov →
mirage7–13-0.0421%1 Nov →
mirage5–13-0.0632%1 Nov →
mirage13–11-0.0611%31 Oct →
ancient13–9-0.0514%31 Oct →
inferno13–5-0.026%31 Oct →
cache13–11-0.029%31 Oct →
ancient13–6-0.0616%31 Oct →
mirage13–2-0.0616%31 Oct →
inferno13–20.0415%31 Oct →
nuke9–50.1126%31 Oct →
inferno6–9-0.1316%31 Oct →
nuke7–13-0.0715%30 Oct →
anubis2–13-0.058%30 Oct →
inferno13–90.1119%29 Oct →
vertigo13–6-0.0422%29 Oct →
anubis13–4-0.0125%29 Oct →
inferno13–110.0120%29 Oct →
dust26–13-0.0224%28 Oct →
nuke13–7-0.0915%28 Oct →
nuke11–130.0120%28 Oct →
dust213–80.0429%28 Oct →
inferno6–13-0.0426%28 Oct →
mirage13–80.0314%28 Oct →
mirage13–8-0.0521%25 Oct →
anubis13–1-0.047%25 Oct →
train13–110.0417%25 Oct →
overpass7–13-0.0311%25 Oct →
ancient13–60.024%22 Oct →
inferno13–50.0122%22 Oct →
mirage13–11-0.0223%22 Oct →
ancient13–9-0.057%19 Oct →
dust211–130.0321%18 Oct →
mirage7–13-0.049%18 Oct →
inferno7–13-0.065%18 Oct →
anubis13–6-0.0812%18 Oct →
mirage13–11-0.0412%18 Oct →
inferno13–11-0.0523%18 Oct →
inferno10–13-0.0524%18 Oct →
dust213–4-0.0314%14 Oct →
ancient10–13-0.008%13 Oct →
nuke10–13-0.0316%13 Oct →
cache7–13-0.0720%8 Oct →
mirage5–13-0.1213%8 Oct →
inferno6–130.0415%6 Oct →
inferno13–11-0.0410%5 Oct →
nuke8–13-0.0526%18 Sept →
mirage9–13-0.0427%18 Sept →
ancient8–13-0.109%15 Sept →
dust23–13-0.087%15 Sept →
mirage10–13-0.0315%15 Sept →
nuke13–9-0.067%14 Sept →
ancient8–130.0118%14 Sept →
dust29–13-0.0717%14 Sept →
mirage1–13-0.104%9 Sept →
mirage6–13-0.0316%5 Sept →
mirage16–13-0.0817%5 Sept →
mirage8–130.0531%5 Sept →
ancient13–16-0.0720%30 Aug →
mirage11–13-0.0026%30 Aug →
nuke9–13-0.0618%23 Jul →
dust213–6-0.0819%23 Jul →
mirage5–13-0.1025%22 Jul →
inferno9–13-0.0721%22 Jul →
vertigo4–13-0.1033%7 Jul →
cache9–13-0.0525%7 Jul →
dust29–13-0.1112%1 Jun →
ancient10–13-0.0620%9 Apr →
ancient2–13-0.116%8 Apr →
nuke13–110.0217%8 Apr →

Match data via Leetify.

Recent teammates

Milestones

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

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