uarasse

uarasse — CS2 Stats

CC76561199098218140[U:1:1137952412]Steam profile ↗✓ No bans

1,317Tracked matches67%Win rate2021Tracked since
CSDB Rating7.2 StrongAll-Rounder
Premier CS Rating12,042Blue band · top ~44.1% of ranked players (population est.)
FaceitLevel 2Top 97.9% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 29 Oct 2026 (7 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: 12,042 -343 5 Jul – 29 Oct · 33 days played
8,42812,643peak 12,6435 Jul29 Oct
12,643Peak Premier in tracked matches
47Days played since 2026-07-05

Premier CS Rating

  • 601 below peak (12,643)
  • +2,043 over 30 days · improving
  • +2,043 over 90 days
  • Next: Purple band at 15,000 — 2,958 to go
  • Reached: Blue band · Light Blue band
  • Light Blue band first seen 2026-09-13

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

Share this profile

CSDB.GGuarasseFACEITLevel 2STANDINGTop 97.9% of rankedPREMIER12,042 · Blue bandcsdb.gg/stats

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Performance scores

Aim83
Positioning66
Utility67

0–100 skill scores via Leetify.

Recent form

HOT51–48–1Last 10051%Win rateWLWWWLWWLW

Last 10 vs previous 10: +10pp win rate · −0.02 avg rating · −8.7pp headshot accuracy · −6ms 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

  • 4–1 · 80% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 22%
  • Avg reaction 528ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 18%
  • Avg reaction 531ms

Last 20

  • 13–7 · 65% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 22%
  • Avg reaction 533ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim8.3
Utility6.7
Positioning6.6
Opening Duels5.6

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

m0NESY

Plays most like m0NESY 90% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: 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

Strengths

T openings. 69% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 69% on T to 46% 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

Aim8.3
Positioning6.6
Utility6.7
Mechanics7.0
Opening Duels6.9
Win Impact10.0

Composite 7.2/10 (Strong), 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 rating0.04+0.02
first ⅓ avg 0.02 → last ⅓ avg 0.04
Reaction time528ms−55ms
first ⅓ avg 583ms → last ⅓ avg 528ms
Headshot accuracy20.8%−1.2%
first ⅓ avg 22.0% → last ⅓ avg 20.8%

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

0.22Best match rating · 9–2 · nuke, 8 Oct →
100%Best headshot accuracy · 0–3 · anubis, 25 Sept →
375msFastest reaction time · 7–9 · inferno, 30 Sept →
13–1Biggest win · mirage, 16 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
5–10In matches decided by ≤2 rounds
8Overtime games

Map breakdown

mirageBest map · 81% over 21infernoWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
mirageS2117–481%0.04
dust2A2011–955%0.02
nukeD165–1131%0.03
anubisA116–555%0.04
cacheB84–450%0.01
ancientC73–443%0.02
infernoD50–50%-0.02
train—41–325%-0.01
vertigo—32–167%0.08
office—21–150%0.01
debris—10–10%0.03
fachwerk—10–10%0.03
overpass—11–0100%-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Skill profile

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

18.3%Headshot accuracy
38.4%Accuracy (enemy spotted)
38.9%Spray accuracy
81.7%Counter-strafing
9.5°Preaim
519msReaction time
68.5%T opening success
46.5%CT opening success
0.58Enemies flashed / flash
10.7%Flash assists
11.59HE damage / grenade
10.24Flashes / match

Recommended for you

Spend your practice time on Inferno

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

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–50.0622%29 Oct →
office10–13-0.0123%29 Oct →
anubis13–70.1217%27 Oct →
anubis13–100.0217%26 Oct →
cache13–20.0329%26 Oct →
dust23–13-0.0315%25 Oct →
mirage13–80.0312%19 Oct →
ancient13–100.0118%19 Oct →
dust25–13-0.0115%17 Oct →
mirage12–20.0312%15 Oct →
nuke9–20.2217%8 Oct →
dust213–6-0.0419%8 Oct →
mirage13–30.1118%7 Oct →
train8–13-0.0011%7 Oct →
inferno7–9-0.0316%30 Sept →
anubis16–130.0819%30 Sept →
nuke13–160.0420%27 Sept →
mirage13–80.0828%27 Sept →
mirage13–50.0422%25 Sept →
anubis0–3-0.06100%25 Sept →
nuke13–70.1429%20 Sept →
mirage13–80.0815%20 Sept →
cache2–10.1350%19 Sept →
inferno5–9-0.0613%19 Sept →
nuke13–90.0423%18 Sept →
anubis13–30.0815%16 Sept →
dust25–130.0419%16 Sept →
mirage13–10.088%16 Sept →
dust213–50.114%9 Sept →
anubis7–130.0410%9 Sept →
mirage13–60.0719%9 Sept →
cache13–10-0.0514%7 Sept →
inferno7–13-0.0117%7 Sept →
dust213–7-0.0813%1 Sept →
mirage13–5-0.078%28 Aug →
cache13–20.119%28 Aug →
cache10–13-0.0121%26 Aug →
cache4–13-0.0616%26 Aug →
mirage10–130.0613%23 Aug →
ancient8–130.0811%22 Aug →
nuke5–130.1123%22 Aug →
mirage13–40.0121%22 Aug →
dust213–9-0.0714%22 Aug →
dust213–110.0412%20 Aug →
anubis6–13-0.0016%19 Aug →
mirage10–80.0114%19 Aug →
dust24–13-0.0117%19 Aug →
nuke7–130.0214%18 Aug →
dust214–16-0.0116%18 Aug →
nuke9–13-0.0534%18 Aug →
mirage13–10.0215%17 Aug →
ancient16–13-0.0213%16 Aug →
mirage13–6-0.0221%16 Aug →
train7–130.0616%16 Aug →
mirage13–110.0914%12 Aug →
dust26–130.0115%12 Aug →
train0–5-0.070%12 Aug →
train13–6-0.0229%12 Aug →
vertigo13–100.0717%5 Aug →
inferno0–13-0.0227%5 Aug →
mirage13–110.0722%5 Aug →
ancient5–13-0.0120%4 Aug →
nuke13–80.0431%2 Aug →
dust213–80.1433%2 Aug →
nuke13–30.0117%2 Aug →
ancient10–130.0217%2 Aug →
mirage13–90.0223%1 Aug →
vertigo13–80.0820%1 Aug →
dust210–130.0424%31 Jul →
nuke2–13-0.0416%31 Jul →
nuke5–9-0.1211%31 Jul →
anubis13–90.0420%31 Jul →
inferno11–130.0123%29 Jul →
mirage10–130.0214%29 Jul →
dust213–30.1020%29 Jul →
dust213–60.1420%29 Jul →
nuke13–16-0.0220%27 Jul →
mirage15–150.0819%27 Jul →
anubis4–130.0127%27 Jul →
anubis9–130.0922%24 Jul →
dust214–160.1317%22 Jul →
anubis13–70.0134%22 Jul →
nuke3–13-0.0524%22 Jul →
dust213–6-0.0427%22 Jul →
mirage13–9-0.0418%15 Jul →
dust211–130.0021%13 Jul →
ancient4–13-0.0219%12 Jul →
cache12–16-0.0620%12 Jul →
mirage13–60.1022%12 Jul →
office13–80.0428%10 Jul →
ancient13–40.1016%9 Jul →
nuke0–20.0450%9 Jul →
debris7–90.0317%9 Jul →
fachwerk2–50.0325%9 Jul →
nuke6–130.0725%8 Jul →
vertigo8–80.0926%7 Jul →
overpass13–5-0.027%6 Jul →
nuke10–130.0118%5 Jul →
dust213–11-0.0324%5 Jul →
cache13–11-0.0133%5 Jul →

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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