rustanu

rustanu — CS2 Stats

LK76561198838406883[U:1:878141155]Steam profile ↗✓ No bans

1,582Tracked matches38%Win rate2021Tracked since
2,110Hours in CS
CSDB Rating5.5 SolidPositional Player
FaceitLevel 8Top 31.2% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (30 days ago). Ranks are recorded once per day this page is viewed.

+100Tracked matches · now 1,582
−8.2ppWin rate · 46.2% → 37.9%

Rating over time

Premier CS Rating: 24,239 +732 3 Jul – 5 Jul · 2 days played
23,50724,239peak 24,2393 Jul5 Jul
24,341Peak Premier in tracked matches
46Days played since 2026-05-20

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

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches91——
Win rate54%——
K/D0.91——
Headshot %53%——

Measured 18 Sep 2026 → 18 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 8 among CSDB-tracked players (n=15,126), 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 8 medianLevel 9 medianvs Level 9
Headshot rate49.4%46.8%48.2%above
Shot accuracy10.4%13.0%13.2%2.9% short
Kill/death ratio0.951.061.070.12 short
Match win rate45.7%46.3%46.9%1.2% short

This profile matches the typical Level 9 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 9 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGrustanuFACEITLevel 8STANDINGTop 31.2% of rankedcsdb.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

Aim75
Positioning56
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY40–50–10Last 10040%Win rateWLWLLLWLWL

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating · +2.1pp headshot accuracy · +13ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 25%
  • Avg reaction 519ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 23%
  • Avg reaction 568ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 22%
  • Avg reaction 561ms

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 (+1.6 against its own average).

Aim7.5
Utility4.5
Positioning5.6
Opening Duels2.5
Clutch3.4

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 95% playstyle similarity

Most alike: positioning profile, utility contribution.

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

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. 567ms 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

Aim7.5
Positioning5.6
Utility4.5
Mechanics6.1
Opening Duels4.0
Win Impact1.0

Composite 5.5/10 (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-0.01−0.03
first ⅓ avg 0.02 → last ⅓ avg -0.01
Reaction time564ms−44ms
first ⅓ avg 608ms → last ⅓ avg 564ms
Headshot accuracy21.5%+2.4%
first ⅓ avg 19.1% → last ⅓ avg 21.5%

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

0.29Best match rating · 9–2 · inferno, 17 Jun →
50%Best headshot accuracy · 9–4 · inferno, 13 Aug →
391msFastest reaction time · 4–9 · inferno, 20 May →
13–0Biggest win · nuke, 11 Oct →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

dust2Best map · 57% over 14ancientWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
mirageD206–1430%-0.01
infernoC198–1142%0.02
dust2A148–657%-0.00
cacheC104–640%0.02
anubisD93–633%-0.03
trainA74–357%0.02
vertigoA74–357%0.06
ancientD51–420%0.01
officeD51–420%-0.01
nuke—21–150%-0.05
overpass—10–10%-0.05
warden—10–10%0.05

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

103,047Lifetime kills
0.95K/D
4,775Matches
45.7%Match win rate
49.4%Headshot % · Top 50% of Level 8 players
10.4%Shot accuracy
10,735MVPs
2,110Hours (in match)
3,128Bombs planted
1,206Bombs defused

Most-used weapons

AK-4738,597
AWP11,163
MP92,651
FAMAS2,022
MAC-101,843

Lifetime map wins

10,870inferno
4,340dust2
2,204nuke
1,737vertigo
863train
367cbble
232office
156lake

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

Faceit stats

Combat

836Matches
51%Win rate
1.17Avg K/D
81.7ADR
46%Headshot %

Clutches & streaks

37%1v1 clutch win
24%1v2 clutch win
8Longest win streak

Recent Faceit resultsLWLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage12147%1.2117.9
Inferno10652%1.2618.3
Dust29447%1.1416.8
Anubis8251%1.2717.6
Ancient7958%1.1216.0
Cache7155%1.2916.7
Nuke2245%1.3218.7
Overpass1050%1.1415.8

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.

22.0%Headshot accuracy
34.9%Accuracy (enemy spotted)
36.9%Spray accuracy
77.3%Counter-strafing
9.4°Preaim
567msReaction time
48.4%T opening success
43.9%CT opening success
0.55Enemies flashed / flash
4.5%Flash assists
6.85HE damage / grenade
6.10Flashes / match

Recommended for you

Spend your practice time on Ancient

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

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–60.0231%17 Oct →
cache5–13-0.0923%17 Oct →
dust213–8-0.0215%17 Oct →
ancient11–130.0727%13 Oct →
anubis6–13-0.0530%11 Oct →
office1–13-0.0312%11 Oct →
nuke13–0-0.0315%11 Oct →
dust211–130.0912%11 Oct →
train13–60.0440%7 Oct →
mirage10–13-0.0129%7 Oct →
nuke7–13-0.0814%4 Oct →
dust213–10-0.0218%4 Oct →
cache13–90.0324%3 Oct →
anubis12–12-0.0115%3 Oct →
inferno0–50.0530%30 Sept →
mirage7–13-0.0441%30 Sept →
dust213–10-0.0317%30 Sept →
cache6–13-0.0424%29 Sept →
anubis6–13-0.0212%29 Sept →
inferno7–130.0516%28 Sept →
mirage9–13-0.0321%27 Sept →
anubis7–13-0.0131%27 Sept →
mirage10–130.0117%24 Sept →
mirage4–13-0.0413%24 Sept →
cache13–90.0618%20 Sept →
cache10–130.0218%19 Sept →
cache13–40.0930%19 Sept →
inferno7–9-0.0314%16 Sept →
anubis13–7-0.0315%16 Sept →
anubis0–6-0.170%16 Sept →
anubis13–70.0346%16 Sept →
mirage13–9-0.0324%8 Sept →
ancient4–13-0.0821%8 Sept →
dust211–130.0022%8 Sept →
office12–12-0.0414%3 Sept →
vertigo12–120.0218%3 Sept →
cache2–13-0.0022%2 Sept →
mirage6–130.0041%2 Sept →
dust213–100.0516%2 Sept →
mirage7–13-0.0117%2 Sept →
cache10–13-0.0122%2 Sept →
mirage15–150.0122%2 Sept →
inferno9–40.1150%13 Aug →
train13–90.0628%12 Aug →
train12–120.0224%12 Aug →
train2–13-0.0726%10 Aug →
train13–90.0218%10 Aug →
dust23–13-0.0315%10 Aug →
mirage11–13-0.0119%29 Jul →
mirage13–100.0423%27 Jul →
mirage10–13-0.0221%25 Jul →
ancient7–13-0.0519%25 Jul →
dust213–11-0.0324%24 Jul →
ancient13–40.1223%24 Jul →
inferno9–60.0822%23 Jul →
office13–110.0523%8 Jul →
office9–130.0417%8 Jul →
mirage6–130.0022%5 Jul →
inferno13–7-0.0519%5 Jul →
mirage13–5-0.068%5 Jul →
mirage13–110.009%3 Jul →
vertigo12–120.0319%25 Jun →
overpass6–13-0.0517%25 Jun →
inferno9–60.0214%24 Jun →
anubis11–130.058%23 Jun →
dust211–13-0.0431%21 Jun →
inferno8–80.0338%17 Jun →
inferno8–80.0628%17 Jun →
train6–13-0.0321%17 Jun →
inferno9–20.2923%17 Jun →
inferno2–9-0.1415%17 Jun →
inferno4–13-0.009%16 Jun →
cache12–120.0319%16 Jun →
mirage13–50.0716%16 Jun →
dust23–13-0.0119%16 Jun →
dust213–9-0.0414%12 Jun →
mirage9–130.0524%12 Jun →
ancient10–13-0.0116%11 Jun →
mirage10–130.0113%11 Jun →
vertigo13–40.1433%8 Jun →
inferno13–110.0219%8 Jun →
inferno13–160.0324%7 Jun →
inferno13–60.0727%6 Jun →
vertigo13–90.0923%5 Jun →
vertigo5–130.0820%5 Jun →
vertigo13–110.0316%5 Jun →
mirage10–13-0.0320%3 Jun →
dust226–28-0.0317%31 May →
mirage13–9-0.0412%31 May →
dust213–110.0210%30 May →
inferno9–5-0.0613%30 May →
anubis13–10-0.0616%30 May →
warden10–130.0515%30 May →
cache13–100.0826%26 May →
office8–13-0.0717%22 May →
inferno14–16-0.0318%22 May →
inferno8–8-0.0517%20 May →
inferno4–9-0.0313%20 May →
vertigo13–3-0.0025%20 May →
train13–40.0934%20 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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.