♱PaTsa♱

♱PaTsa♱ — CS2 Stats

GR76561199685651397[U:1:1725385669]Steam profile ↗✓ No bans

142Tracked matches37%Win rate2026Tracked since
1,471Hours in CS61Hrs last 2 wks
CSDB Rating3.8 LearningPositional Player
Premier CS Rating10,221Blue band · top ~53.7% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 17 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: 10,221 -10,798 26 Apr – 17 Oct · 40 days played
8,93723,412peak 23,41226 Apr17 Oct
23,412Peak Premier in tracked matches
47Days played since 2026-04-26

Premier CS Rating

  • 13,191 below peak (23,412)
  • +100 over 30 days · steady
  • +1,284 over 90 days
  • Next: Purple band at 15,000 — 4,779 to go
  • Reached: Pink band · 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 Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate35.2%42.0%44.3%9.1% short
Shot accuracy0.0%9.6%11.9%11.9% short
Kill/death ratio1.290.981.03above
Match win rate58.4%43.8%45.2%above

This profile matches the typical Purple band player on 2 of 4 comparable metrics.

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

Share this profile

CSDB.GG♱PaTsa♱PREMIER10,221 · Blue bandcsdb.gg/stats

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Performance scores

Aim56
Positioning54
Utility27

0–100 skill scores via Leetify.

Recent form

COLD49–50–1Last 10049%Win rateLLWWLLLLLL

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · +1.5pp headshot accuracy · +70ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 12%
  • Avg reaction 666ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 10%
  • Avg reaction 618ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 10%
  • Avg reaction 583ms

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 (+2 against its own average).

Aim5.6
Utility2.7
Positioning5.4
Opening Duels2.1

Strong CT-side openerLimited 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 89% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

T-side openings. Opening success drops from 47% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 594ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.6
Positioning5.4
Utility2.7
Mechanics3.7
Opening Duels2.4
Win Impact0.6

Composite 3.8/10 (Learning), 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 rating0.00−0.07
first ⅓ avg 0.07 → last ⅓ avg 0.00
Reaction time598ms+120ms
first ⅓ avg 478ms → last ⅓ avg 598ms
Headshot accuracy9.9%−7.8%
first ⅓ avg 17.7% → last ⅓ avg 9.9%

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 · 13–5 · nuke, 11 Jul →
71%Best headshot accuracy · 7–6 · mirage, 23 Jun →
344msFastest reaction time · 13–11 · mirage, 30 Apr →
13–2Biggest win · nuke, 19 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L2Current streak
9–4In matches decided by ≤2 rounds
3Overtime games

Map breakdown

mirageBest map · 65% over 31dust2Weakest map · 27% over 22
MapGradePlayedRecordWin rateAvg rating
mirageS3120–1165%0.04
dust2D226–1627%0.00
infernoA138–562%0.05
anubisA116–555%0.01
nukeC73–443%-0.02
ancientB63–350%0.01
cacheD62–433%0.06
overpass—31–233%0.08
train—10–10%-0.07

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (27% over 22). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

7,139Lifetime kills
1.29K/D · Top 10% of Blue band
459Matches
58.4%Match win rate · Top 5% of Blue band
35.2%Headshot %
0.0%Shot accuracy
1,316MVPs
153Hours (in match)
888Bombs planted
103Bombs defused

Most-used weapons

Lifetime map wins

1,101dust2
729inferno
262nuke
75train
26vertigo

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.

10.0%Headshot accuracy
37.8%Accuracy (enemy spotted)
36.2%Spray accuracy
66.6%Counter-strafing
8.7°Preaim
594msReaction time
31.6%T opening success
47.2%CT opening success
0.17Enemies flashed / flash
0.0%Flash assists
15.80HE damage / grenade
0.61Flashes / 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 9.9896% — below the 15% mark we flag

    Aim Training →
  2. 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 0.1665 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 31.6327% — below the 40% mark we flag

Spend your practice time on Dust 2

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

27% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient11–130.019%17 Oct →
dust23–13-0.0413%16 Oct →
mirage13–90.0115%16 Oct →
mirage13–100.0211%16 Oct →
dust24–130.0014%12 Oct →
cache4–130.0915%12 Oct →
mirage5–13-0.005%12 Oct →
dust27–13-0.015%11 Oct →
anubis5–12-0.066%11 Oct →
dust24–13-0.0110%11 Oct →
anubis3–13-0.078%9 Oct →
cache13–100.1712%6 Oct →
mirage13–90.109%5 Oct →
ancient13–110.058%5 Oct →
cache7–130.035%5 Oct →
mirage9–13-0.077%5 Oct →
anubis3–13-0.017%5 Oct →
dust29–130.0510%3 Oct →
nuke4–13-0.113%3 Oct →
dust213–10-0.0219%3 Oct →
dust25–13-0.0311%30 Sept →
nuke5–13-0.040%30 Sept →
dust213–8-0.025%30 Sept →
inferno9–130.0012%27 Sept →
mirage13–10-0.0210%27 Sept →
dust24–13-0.0318%26 Sept →
inferno13–3-0.059%26 Sept →
anubis8–130.0011%25 Sept →
mirage13–80.0114%25 Sept →
inferno13–40.1217%20 Sept →
anubis13–30.048%19 Sept →
inferno13–70.0211%19 Sept →
mirage10–13-0.0110%11 Sept →
dust213–110.0215%10 Sept →
ancient12–16-0.0211%10 Sept →
inferno13–110.0611%9 Sept →
mirage3–130.0156%8 Sept →
ancient6–130.0225%8 Sept →
mirage2–13-0.0514%8 Sept →
mirage13–100.0215%2 Sept →
anubis2–13-0.0614%2 Sept →
cache13–9-0.0220%2 Sept →
dust21–13-0.0614%2 Sept →
nuke13–3-0.0317%2 Sept →
inferno8–130.0619%30 Aug →
mirage13–110.0621%30 Aug →
dust28–130.0719%30 Aug →
dust210–13-0.0913%29 Aug →
mirage7–130.0917%25 Aug →
mirage13–60.0226%25 Aug →
cache10–130.0017%25 Aug →
anubis13–70.0413%25 Aug →
cache8–130.079%25 Aug →
ancient13–80.0617%24 Aug →
mirage11–13-0.0111%24 Aug →
inferno13–100.0915%24 Aug →
mirage2–13-0.074%21 Aug →
nuke3–13-0.105%21 Aug →
nuke13–2-0.040%19 Aug →
ancient13–8-0.0717%15 Aug →
train8–13-0.0714%12 Aug →
mirage16–130.0310%21 Jul →
anubis13–110.0812%20 Jul →
dust210–13-0.0413%16 Jul →
nuke13–50.2214%11 Jul →
inferno6–9-0.0820%3 Jul →
mirage13–5-0.019%30 Jun →
mirage7–60.1071%23 Jun →
dust24–13-0.064%23 Jun →
inferno13–70.0216%23 Jun →
dust21–13-0.048%19 Jun →
mirage13–60.1510%15 Jun →
anubis13–40.1124%15 Jun →
mirage11–130.1419%12 Jun →
dust213–60.0513%12 Jun →
mirage13–100.0615%12 Jun →
overpass13–50.0516%12 Jun →
overpass8–130.0911%11 Jun →
mirage6–130.1022%11 Jun →
anubis13–80.1023%11 Jun →
dust26–13-0.0123%9 Jun →
mirage9–130.1529%7 Jun →
mirage13–80.1817%7 Jun →
dust215–150.1024%6 Jun →
mirage13–110.1314%5 Jun →
overpass5–130.0918%5 Jun →
mirage13–90.1118%5 Jun →
inferno13–110.1713%2 Jun →
inferno8–130.0823%2 Jun →
mirage13–40.1428%2 Jun →
dust29–130.0235%2 Jun →
inferno11–130.0213%1 Jun →
mirage13–11-0.0611%30 Apr →
anubis13–2-0.040%30 Apr →
nuke0–7-0.020%30 Apr →
mirage13–5-0.0023%29 Apr →
dust213–50.057%29 Apr →
dust213–40.1213%26 Apr →
inferno13–20.178%26 Apr →
mirage13–40.0420%26 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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