яıcσ l ICH SPIEL MIT HASS

яıcσ l ICH SPIEL MIT HASS — CS2 Stats

DE76561198109555824[U:1:149290096]Steam profile ↗✓ No bans

739Tracked matches60%Win rate2020Tracked since
2,377Hours in CS31Hrs last 2 wks
CSDB Rating5.5 SolidSupport
Premier CS Rating18,215Purple band · top ~15.6% of ranked players (population est.)
FaceitLevel 1Top 100.0% of ranked FACEIT players
WingmanGold Nova III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Oct 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: 18,215 +7,173 24 Jul – 30 Oct · 22 days played
9,48318,215peak 18,21524 Jul30 Oct
18,215Peak Premier in tracked matches
28Days played since 2026-07-24

Premier CS Rating

  • At peak — 18,215
  • +5,890 over 30 days · improving
  • +7,510 over 90 days
  • Next: Pink band at 20,000 — 1,785 to go
  • Reached: Purple band · Blue band · Light Blue band

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 1 among CSDB-tracked players (n=2,367), 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 1 medianLevel 2 medianvs Level 2
Headshot rate45.3%40.9%41.3%above
Shot accuracy14.2%14.2%12.7%above
Kill/death ratio1.540.950.95above
Match win rate37.4%42.1%42.6%5.2% short

This profile matches the typical Level 2 player on 3 of 4 comparable metrics.

Widest gap: Match win rate. That is the metric furthest from the Level 2 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGяıcσ l ICH SPIEL MIT HASSFACEITLevel 1STANDINGTop 100.0% of rankedPREMIER18,215 · Purple 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
Positioning44
Utility70

0–100 skill scores via Leetify.

Recent form

HOT51–46–3Last 10051%Win rateWWWWLWLWWW

Last 10 vs previous 10: +40pp win rate · −0.03 avg rating · −1.4pp headshot accuracy · +29ms reaction

Win rate up 40pp 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 (−0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 11%
  • Avg reaction 482ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 12%
  • Avg reaction 532ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 518ms

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 (+2.8 against its own average).

Aim5.8
Utility7.0
Positioning4.4
Opening Duels1.1

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 70% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim5.8
Positioning4.4
Utility7.0
Mechanics5.7
Opening Duels1.8
Win Impact8.3

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-0.02−0.03
first ⅓ avg 0.01 → last ⅓ avg -0.02
Reaction time513ms+14ms
first ⅓ avg 499ms → last ⅓ avg 513ms
Headshot accuracy11.8%−5.4%
first ⅓ avg 17.1% → last ⅓ avg 11.8%

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

0.18Best match rating · 9–3 · nuke, 6 Oct →
57%Best headshot accuracy · 6–1 · mirage, 6 Oct →
344msFastest reaction time · 6–0 · anubis, 22 Oct →
13–1Biggest win · cache, 27 Oct →

Across the last 100 tracked matches.

Highlights

7Longest win streak
W4Current streak
7–3In matches decided by ≤2 rounds
8Overtime games

Map breakdown

anubisBest map · 92% over 12ancientWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
cacheA2313–1057%0.00
dust2C188–1044%-0.00
infernoC156–940%-0.02
anubisS1211–192%-0.01
mirageD113–827%-0.03
nukeS76–186%0.01
ancientD61–517%-0.01
office—21–150%-0.01
train—21–150%-0.01
vertigo—21–150%-0.00
rush_001—10–10%-0.13
boulder—10–10%-0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

90,278Lifetime kills
1.54K/D · Top 5% of Level 1 players
3,218Matches
37.4%Match win rate
45.3%Headshot % · Top 50% of Level 1 players
14.2%Shot accuracy
7,828MVPs
1,176Hours (in match)
4,570Bombs planted
548Bombs defused

Most-used weapons

AK-4716,989
MAG-714,988
Tec-911,260
AWP8,026
SSG 083,159
P901,758

Lifetime map wins

9,400dust2
3,568inferno
959nuke
651vertigo
493office
394cbble
380train
170lake

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

Faceit stats

Combat

34Matches
29%Win rate
0.75Avg K/D
—ADR
43%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
4Longest win streak

Recent Faceit resultsLWWWW

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.

12.8%Headshot accuracy
30.4%Accuracy (enemy spotted)
34.3%Spray accuracy
75.5%Counter-strafing
9.5°Preaim
525msReaction time
36.8%T opening success
37.3%CT opening success
0.62Enemies flashed / flash
3.4%Flash assists
9.49HE damage / grenade
17.93Flashes / 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. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 12.79% — below the 15% mark we flag

    Aim Training →
  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 36.7745% — below the 40% mark we flag

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.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–70.0313%30 Oct →
nuke13–2-0.069%30 Oct →
anubis13–7-0.0614%30 Oct →
anubis13–20.0212%30 Oct →
mirage10–13-0.089%30 Oct →
cache13–7-0.0012%29 Oct →
cache6–13-0.019%29 Oct →
cache13–11-0.0215%29 Oct →
anubis13–11-0.0810%29 Oct →
cache10–3-0.0320%29 Oct →
mirage5–13-0.0715%29 Oct →
cache13–7-0.018%29 Oct →
office13–100.039%29 Oct →
cache13–10.1016%27 Oct →
cache13–40.1724%27 Oct →
cache5–130.0610%27 Oct →
mirage7–13-0.0815%27 Oct →
dust23–13-0.0811%27 Oct →
cache0–5-0.0310%26 Oct →
ancient12–16-0.0618%26 Oct →
cache4–13-0.049%26 Oct →
anubis13–9-0.0314%26 Oct →
anubis13–50.0115%26 Oct →
cache13–10-0.0120%26 Oct →
dust26–13-0.0610%26 Oct →
cache10–13-0.059%23 Oct →
cache8–13-0.0616%22 Oct →
mirage13–4-0.069%22 Oct →
anubis6–00.010%22 Oct →
inferno13–7-0.0614%22 Oct →
dust29–13-0.120%22 Oct →
dust213–100.0015%22 Oct →
inferno5–13-0.050%19 Oct →
dust210–13-0.0316%19 Oct →
mirage1–13-0.0425%19 Oct →
inferno7–13-0.0717%19 Oct →
anubis12–5-0.028%18 Oct →
mirage8–13-0.0410%18 Oct →
cache3–13-0.1011%18 Oct →
nuke16–14-0.038%18 Oct →
cache13–80.044%16 Oct →
inferno13–60.012%16 Oct →
ancient13–80.0111%16 Oct →
inferno13–70.0317%16 Oct →
dust213–7-0.0114%16 Oct →
cache13–60.009%16 Oct →
ancient9–13-0.0516%15 Oct →
nuke13–30.0646%15 Oct →
anubis16–130.0116%15 Oct →
inferno4–13-0.1016%13 Oct →
rush_0010–4-0.130%13 Oct →
dust25–130.044%13 Oct →
anubis13–10-0.0412%13 Oct →
dust26–130.0211%13 Oct →
ancient10–13-0.038%12 Oct →
office6–13-0.0413%12 Oct →
ancient12–160.057%8 Oct →
cache13–60.0112%8 Oct →
cache13–50.088%8 Oct →
anubis13–6-0.009%8 Oct →
ancient4–130.0010%7 Oct →
boulder10–13-0.003%7 Oct →
train13–9-0.0115%7 Oct →
train8–13-0.029%7 Oct →
dust210–130.0116%6 Oct →
mirage6–10.0357%6 Oct →
dust216–140.0623%6 Oct →
cache13–90.036%6 Oct →
nuke9–30.1811%6 Oct →
vertigo6–13-0.0215%26 Sept →
dust29–13-0.0325%23 Sept →
inferno11–13-0.0621%23 Sept →
mirage6–13-0.0212%21 Sept →
dust213–100.0412%21 Sept →
inferno13–40.1415%20 Sept →
inferno6–9-0.0716%20 Sept →
nuke13–7-0.0333%20 Sept →
inferno5–13-0.058%20 Sept →
dust213–7-0.0214%20 Sept →
dust213–90.0120%20 Sept →
dust213–1-0.0038%20 Sept →
anubis12–12-0.0419%20 Sept →
dust214–160.1023%18 Sept →
anubis13–90.1216%18 Sept →
inferno11–13-0.0216%17 Sept →
mirage9–130.0323%10 Sept →
inferno13–90.0811%10 Sept →
inferno13–110.002%10 Sept →
vertigo13–110.0212%1 Sept →
dust212–120.0327%27 Aug →
cache12–120.0519%26 Aug →
cache10–13-0.0421%26 Aug →
cache3–13-0.078%26 Aug →
mirage16–14-0.0011%10 Aug →
inferno1–13-0.1415%10 Aug →
inferno7–13-0.0129%10 Aug →
nuke13–10-0.0216%10 Aug →
nuke13–16-0.0114%10 Aug →
mirage8–130.0321%28 Jul →
dust213–9-0.0015%24 Jul →

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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