слава украйни

слава украйни — CS2 Stats

76561199467042718[U:1:1506776990]Steam profile ↗✓ No bans

232Tracked matches66%Win rate2023Tracked since
321Hours in CS
CSDB Rating7.6 StrongPositional Player
Premier CS Rating25,100Top 25% of 210,584 CSDB-tracked playersRed band · top ~3% of ranked players (population est.)
CSDB Leaderboard#20678 of 257741 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Oct 2026 (9 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: 25,100 +7,708 21 May – 18 Oct · 17 days played
16,70325,100peak 25,10021 May18 Oct
25,101Peak Premier in tracked matches
34Days played since 2026-04-17

Premier CS Rating

  • At peak — 25,100
  • +5,814 over 30 days · improving
  • +8,397 over 90 days
  • Next: Gold band at 30,000 — 4,900 to go
  • Reached: Red band · Pink band · Purple band · Blue band
  • Purple band first seen 2026-09-24
  • Blue band first seen 2026-09-24

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 Red band among CSDB-tracked players (n=13,318), 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 playerRed band medianGold band medianvs Gold band
Headshot rate46.2%49.3%50.9%4.7% short
Shot accuracy5.4%13.4%11.8%6.4% short
Kill/death ratio1.101.121.180.08 short
Match win rate46.9%48.5%51.9%5.0% short

This profile sits below the typical Gold band player on every metric we can compare.

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

Share this profile

CSDB.GGслава украйниPREMIER25,100 · Red 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

Aim84
Positioning67
Utility60

0–100 skill scores via Leetify.

Recent form

STEADY58–38–4Last 10058%Win rateTWWWWLLWWL

Last 10 vs previous 10: 0pp win rate · +0.02 avg rating · +0.0pp headshot accuracy · +66ms reaction

Win rate 0pp 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

  • 4–0–1 · 80% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 24%
  • Avg reaction 598ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 24%
  • Avg reaction 581ms

Last 20

  • 12–7–1 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 24%
  • Avg reaction 548ms

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 against its own average).

Aim8.4
Utility6.0
Positioning6.7
Opening Duels4.5

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

jL

Plays most like jL 94% playstyle similarity

Most alike: utility contribution, positioning 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

T openings. 67% T opening-duel success — entries that actually open the round.

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.

CT openings. Opening success drops from 67% on T to 42% on CT — first contacts on the defending side are being lost.

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

Aim8.4
Positioning6.7
Utility6.0
Mechanics5.9
Opening Duels6.2
Win Impact10.0

Composite 7.6/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.01
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time555ms−57ms
first ⅓ avg 612ms → last ⅓ avg 555ms
Headshot accuracy22.7%+2.0%
first ⅓ avg 20.7% → last ⅓ avg 22.7%

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

0.15Best match rating · 13–0 · mirage, 19 Aug →
67%Best headshot accuracy · 13–5 · dust2, 13 Jul →
328msFastest reaction time · 0–13 · mirage, 12 Aug →
13–0Biggest win · mirage, 19 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
6–5In matches decided by ≤2 rounds
7Overtime games

Map breakdown

ancientBest map · 88% over 16trainWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
dust2A2313–1057%0.02
ancientS1614–288%0.05
mirageB158–753%-0.01
cacheA149–564%0.02
infernoB115–645%-0.00
anubisC83–538%-0.01
nukeB63–350%0.00
trainD62–433%0.02
vertigo—11–0100%0.00

Across the last 100 tracked matches.

Lifetime stats

18,207Lifetime kills
1.10K/D
868Matches
46.9%Match win rate
46.2%Headshot %
5.4%Shot accuracy
1,905MVPs
321Hours (in match)
587Bombs planted
221Bombs defused

Most-used weapons

Lifetime map wins

1,352inferno
1,212dust2
520nuke
348vertigo
196train
131office
15lake
9cbble

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.

22.6%Headshot accuracy
38.7%Accuracy (enemy spotted)
43.4%Spray accuracy
76.5%Counter-strafing
10.1°Preaim
543msReaction time
67.5%T opening success
41.9%CT opening success
0.64Enemies flashed / flash
4.5%Flash assists
5.78HE damage / grenade
8.75Flashes / match

Recommended for you

Spend your practice time on Train

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.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
dust212–120.0517%21 Oct →
cache13–6-0.0610%21 Oct →
cache13–90.0523%21 Oct →
inferno13–6-0.0244%18 Oct →
cache16–130.0128%18 Oct →
mirage10–13-0.0719%18 Oct →
dust21–130.0030%18 Oct →
ancient13–70.1226%18 Oct →
anubis16–140.0425%18 Oct →
dust210–13-0.0218%17 Oct →
ancient16–13-0.0120%17 Oct →
nuke13–20.0628%17 Oct →
cache5–130.0335%17 Oct →
inferno9–130.0825%16 Oct →
inferno11–13-0.0230%16 Oct →
mirage13–3-0.0430%16 Oct →
dust213–8-0.019%16 Oct →
ancient13–7-0.0023%16 Oct →
inferno1–9-0.1325%16 Oct →
mirage13–6-0.0315%16 Oct →
inferno13–3-0.0319%16 Oct →
ancient11–130.0220%15 Oct →
cache9–130.0115%15 Oct →
nuke13–11-0.0215%15 Oct →
cache13–60.0124%15 Oct →
ancient13–70.0627%14 Oct →
dust213–60.0324%14 Oct →
inferno8–0-0.0529%14 Oct →
ancient13–50.0319%14 Oct →
anubis5–13-0.0419%14 Oct →
nuke5–130.0021%14 Oct →
inferno5–130.0614%14 Oct →
dust213–90.0723%14 Oct →
nuke13–70.0319%14 Oct →
inferno13–30.0922%10 Oct →
dust213–10.0112%10 Oct →
inferno10–13-0.0214%10 Oct →
dust214–160.0020%10 Oct →
cache10–13-0.0123%10 Oct →
nuke8–13-0.0624%10 Oct →
nuke10–13-0.0121%10 Oct →
dust213–70.0719%10 Oct →
dust21–13-0.0243%10 Oct →
dust211–130.0029%10 Oct →
anubis13–40.0117%8 Oct →
dust213–60.0433%8 Oct →
mirage10–13-0.0230%8 Oct →
cache10–130.0220%8 Oct →
train9–13-0.0130%7 Oct →
train7–130.0828%7 Oct →
ancient13–90.1026%7 Oct →
train13–80.0322%7 Oct →
ancient13–4-0.0121%1 Oct →
ancient13–40.1322%1 Oct →
dust216–140.0327%1 Oct →
ancient13–2-0.0317%1 Oct →
dust29–130.0427%30 Sept →
anubis13–80.0114%16 Sept →
anubis0–3-0.070%16 Sept →
anubis3–13-0.0518%16 Sept →
mirage13–110.0119%15 Sept →
ancient13–10.0832%26 Aug →
cache10–10.1146%26 Aug →
cache13–40.0338%26 Aug →
inferno12–12-0.0312%19 Aug →
mirage13–00.1523%19 Aug →
train1–130.0040%12 Aug →
dust21–13-0.008%12 Aug →
mirage0–13-0.070%12 Aug →
mirage13–10-0.0215%12 Aug →
ancient13–9-0.0120%1 Aug →
dust211–130.0321%1 Aug →
cache13–40.0230%1 Aug →
dust213–70.1224%1 Aug →
mirage6–13-0.0419%1 Aug →
anubis9–13-0.0120%22 Jul →
ancient13–70.0622%16 Jul →
dust20–13-0.1023%15 Jul →
ancient13–00.0237%14 Jul →
dust213–5-0.1167%13 Jul →
mirage15–15-0.200%12 Jul →
mirage13–2-0.0234%12 Jul →
dust213–6-0.037%11 Jul →
inferno13–80.0319%11 Jul →
mirage15–15-0.0223%10 Jul →
cache0–13-0.0229%1 Jul →
mirage13–110.1325%26 Jun →
dust213–40.0317%26 Jun →
ancient6–130.1018%12 Jun →
dust213–50.1314%12 Jun →
mirage13–40.0918%12 Jun →
vertigo13–80.0018%3 Jun →
anubis9–130.0016%30 May →
dust213–100.1022%21 May →
ancient13–40.0916%21 May →
cache13–4-0.008%9 May →
cache2–00.0233%9 May →
train13–9-0.0213%22 Apr →
train9–130.0419%22 Apr →
mirage4–130.0729%17 Apr →

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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