OKT • helwi

OKT • helwi — CS2 Stats

DE76561198174371501[U:1:214105773]Steam profile ↗✓ No bans

1,349Tracked matches43%Win rate2021Tracked since
3,910Hours in CS5Hrs last 2 wks
CSDB Rating4.4 DevelopingPositional Player
Premier CS Rating14,240Blue band · top ~32.4% of ranked players (population est.)
FaceitLevel 2Top 97.9% of ranked FACEIT players
WingmanLegendary Eagle Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Oct 2026 (12 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: 14,240 +495 23 Aug – 18 Oct · 17 days played
13,35314,470peak 14,47023 Aug18 Oct
14,470Peak Premier in tracked matches
38Days played since 2026-08-06

Premier CS Rating

  • 230 below peak (14,470)
  • +370 over 30 days · steady
  • Next: Purple band at 15,000 — 760 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-01
  • Light Blue band first seen 2026-09-01

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 2 among CSDB-tracked players (n=6,128), 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 2 medianLevel 3 medianvs Level 3
Headshot rate42.2%41.3%41.8%meets
Shot accuracy17.9%12.7%12.2%above
Kill/death ratio1.100.950.98above
Match win rate38.0%42.6%43.3%5.3% short

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

Widest gap: Match win rate. That is the metric furthest from the Level 3 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGOKT • helwiFACEITLevel 2STANDINGTop 97.9% of rankedPREMIER14,240 · 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

Aim58
Positioning51
Utility16

0–100 skill scores via Leetify.

Recent form

COLD32–62–6Last 10032%Win rateWWWLLTLLLL

Last 10 vs previous 10: −30pp win rate · +0.00 avg rating · +6.2pp headshot accuracy · +77ms reaction

Win rate down 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 (+0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 23%
  • Avg reaction 659ms

Last 10

  • 3–6–1 · 30% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 23%
  • Avg reaction 682ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 19%
  • Avg reaction 643ms

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 (+1.7 against its own average).

Aim5.8
Utility1.6
Positioning5.1
Opening Duels3.5

Limited utility dependence

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

donk

Plays most like donk 91% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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

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

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

Aim5.8
Positioning5.1
Utility1.6
Mechanics5.7
Opening Duels5.2
Win Impact2.6

Composite 4.4/10 (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 rating0.00+0.00
first ⅓ avg -0.00 → last ⅓ avg 0.00
Reaction time632ms+32ms
first ⅓ avg 601ms → last ⅓ avg 632ms
Headshot accuracy20.2%+4.2%
first ⅓ avg 16.0% → last ⅓ avg 20.2%

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 · 9–5 · inferno, 3 Oct →
41%Best headshot accuracy · 7–13 · nuke, 2 Oct →
453msFastest reaction time · 10–13 · office, 26 Sept →
13–2Biggest win · dust2, 23 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W3Current streak
3–5In matches decided by ≤2 rounds
4Overtime games

Map breakdown

vertigoBest map · 60% over 5cacheWeakest map · 20% over 10
MapGradePlayedRecordWin rateAvg rating
dust2D196–1332%-0.02
infernoD134–931%0.01
ancientD113–827%-0.03
cacheD102–820%-0.01
nukeD102–820%0.02
mirageD93–633%-0.02
anubisD72–529%-0.01
trainD62–433%0.01
vertigoA53–260%-0.03
boulder—32–167%-0.01
italy—20–20%-0.05
office—20–20%0.00
shelter—11–0100%0.02
fachwerk—11–0100%0.07
overpass—11–0100%-0.05

Across the last 100 tracked matches.

Lifetime stats

133,932Lifetime kills
1.10K/D · Top 25% of Level 2 players
7,121Matches
38.0%Match win rate
42.2%Headshot % · Top 50% of Level 2 players
17.9%Shot accuracy · Top 25% of Level 2 players
11,508MVPs
2,318Hours (in match)
3,726Bombs planted
1,101Bombs defused

Most-used weapons

AK-4732,027
AWP12,424
FAMAS4,239
Tec-94,025
P903,528

Lifetime map wins

9,540dust2
8,645nuke
5,326inferno
1,781office
1,699train
1,458vertigo
1,438cbble
1,313militia

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

Faceit stats

Combat

56Matches
45%Win rate
0.91Avg K/D
—ADR
41%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
6Longest win streak

Recent Faceit resultsLWLLW

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.

20.5%Headshot accuracy
30.6%Accuracy (enemy spotted)
34.0%Spray accuracy
75.5%Counter-strafing
9.5°Preaim
632msReaction time
54.9%T opening success
46.3%CT opening success
0.12Enemies flashed / flash
2.4%Flash assists
12.23HE damage / grenade
0.31Flashes / 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 0.1232 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Cache

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

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
shelter13–40.0218%27 Oct →
dust213–20.0329%23 Oct →
dust213–6-0.0120%23 Oct →
dust25–13-0.0620%23 Oct →
anubis3–130.0131%18 Oct →
italy12–12-0.0510%17 Oct →
train8–130.0121%17 Oct →
cache9–130.0421%17 Oct →
cache6–13-0.0328%13 Oct →
train6–130.0329%13 Oct →
boulder13–10-0.0218%13 Oct →
mirage13–40.0917%11 Oct →
nuke9–130.0312%10 Oct →
boulder12–12-0.0313%8 Oct →
vertigo13–6-0.0911%8 Oct →
inferno7–13-0.0513%3 Oct →
inferno3–13-0.0524%3 Oct →
ancient13–6-0.0516%3 Oct →
inferno13–40.0520%3 Oct →
inferno9–50.1021%3 Oct →
dust26–130.0122%2 Oct →
nuke7–130.0841%2 Oct →
dust29–13-0.0728%2 Oct →
dust29–130.0224%2 Oct →
nuke13–70.0724%30 Sept →
anubis13–30.0216%30 Sept →
cache6–13-0.0326%29 Sept →
ancient5–13-0.0223%29 Sept →
fachwerk13–80.0720%27 Sept →
boulder13–50.0215%27 Sept →
office10–13-0.0216%26 Sept →
ancient7–13-0.0117%24 Sept →
dust213–10-0.047%24 Sept →
cache13–10-0.069%22 Sept →
vertigo13–90.0031%22 Sept →
cache13–60.0413%21 Sept →
ancient3–13-0.0415%21 Sept →
vertigo12–7-0.0424%20 Sept →
anubis2–130.0125%20 Sept →
inferno0–13-0.0936%19 Sept →
nuke5–13-0.0315%19 Sept →
overpass13–5-0.0515%19 Sept →
dust29–13-0.0420%19 Sept →
mirage13–8-0.0427%19 Sept →
vertigo5–13-0.0117%19 Sept →
ancient11–13-0.0221%19 Sept →
dust213–60.0416%18 Sept →
dust28–130.0327%17 Sept →
dust213–7-0.0620%17 Sept →
dust27–13-0.0713%6 Sept →
italy3–13-0.0617%6 Sept →
cache3–13-0.0730%6 Sept →
mirage7–13-0.0214%6 Sept →
train13–10-0.0118%6 Sept →
dust215–15-0.0313%6 Sept →
mirage4–13-0.093%6 Sept →
ancient13–9-0.069%6 Sept →
nuke6–130.0238%5 Sept →
office4–130.0341%5 Sept →
anubis6–13-0.0315%4 Sept →
vertigo3–13-0.0331%28 Aug →
cache12–120.0116%28 Aug →
nuke7–130.0217%28 Aug →
mirage1–13-0.078%27 Aug →
nuke15–15-0.0416%26 Aug →
anubis4–13-0.0311%26 Aug →
anubis16–14-0.0713%23 Aug →
dust22–13-0.1310%23 Aug →
mirage13–11-0.0121%23 Aug →
inferno11–130.0217%21 Aug →
nuke8–13-0.0111%21 Aug →
dust25–13-0.0525%21 Aug →
ancient1–13-0.0128%21 Aug →
inferno9–130.0914%21 Aug →
dust211–13-0.0420%20 Aug →
ancient13–110.0515%20 Aug →
mirage10–13-0.0719%20 Aug →
ancient11–13-0.0918%20 Aug →
mirage7–13-0.0421%20 Aug →
ancient2–130.0014%19 Aug →
dust210–130.0415%19 Aug →
inferno9–130.0113%17 Aug →
train4–120.0311%17 Aug →
cache7–130.0216%16 Aug →
inferno3–130.0311%16 Aug →
train1–13-0.0426%15 Aug →
cache10–13-0.0916%14 Aug →
dust28–3-0.030%14 Aug →
inferno13–80.0414%14 Aug →
inferno9–130.0415%14 Aug →
anubis9–13-0.019%14 Aug →
nuke11–130.0216%13 Aug →
inferno13–6-0.060%13 Aug →
nuke13–50.0113%13 Aug →
train13–60.0416%13 Aug →
mirage4–130.0621%10 Aug →
dust29–130.0521%10 Aug →
cache12–160.0421%10 Aug →
inferno12–120.0420%6 Aug →
ancient7–13-0.0420%6 Aug →

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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