Pahe

Pahe — CS2 Stats

76561198080324969[U:1:120059241]Steam profile ↗✓ No bans

374Tracked matches39%Win rate2020Tracked since
1,551Hours in CS78Hrs last 2 wks
CSDB Rating5.2 DevelopingPositional Player
Premier CS Rating11,597Blue band · top ~46.4% of ranked players (population est.)
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Nov 2026 (2 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: 11,597 +91 15 Aug – 3 Nov · 46 days played
8,83913,149peak 13,14915 Aug3 Nov
13,149Peak Premier in tracked matches
48Days played since 2026-08-15

Premier CS Rating

  • 1,552 below peak (13,149)
  • -186 over 30 days · steady
  • +91 over 90 days
  • Next: Purple band at 15,000 — 3,403 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-24
  • Light 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 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 rate40.3%42.0%44.4%4.1% short
Shot accuracy8.5%9.6%11.9%3.4% short
Kill/death ratio0.760.981.030.27 short
Match win rate37.6%43.8%45.2%7.6% short

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

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.GGPahePREMIER11,597 · Blue bandcsdb.gg/stats

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Performance scores

Aim69
Positioning68
Utility21

0–100 skill scores via Leetify.

Recent form

STEADY38–59–3Last 10038%Win rateLLWLWLTWWL

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · −0.1pp headshot accuracy · −24ms reaction

Win rate up 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 -0.01
  • Avg headshot accuracy 15%
  • Avg reaction 548ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 14%
  • Avg reaction 568ms

Last 20

  • 6–12–2 · 30% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 14%
  • Avg reaction 580ms

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 (+3.1 against its own average).

Aim6.9
Utility2.1
Positioning6.8
Opening Duels4.0
Clutch1.8

Limited 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 79% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower aim profile; lower utility contribution.

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. 77% T opening-duel success — entries that actually open the round.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

CT openings. Opening success drops from 77% on T to 46% on CT — first contacts on the defending side are being lost.

Reaction time. 600ms 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

Aim6.9
Positioning6.8
Utility2.1
Mechanics5.9
Opening Duels7.1
Win Impact1.4

Composite 5.2/10 (Developing), 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 rating-0.01+0.03
first ⅓ avg -0.05 → last ⅓ avg -0.01
Reaction time594ms−27ms
first ⅓ avg 621ms → last ⅓ avg 594ms
Headshot accuracy14.6%−1.5%
first ⅓ avg 16.1% → last ⅓ avg 14.6%

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

0.10Best match rating · 6–13 · cache, 12 Oct →
36%Best headshot accuracy · 13–3 · anubis, 27 Sept →
422msFastest reaction time · 13–3 · anubis, 27 Sept →
13–2Biggest win · nuke, 18 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L2Current streak
8–8In matches decided by ≤2 rounds
11Overtime games

Map breakdown

anubisBest map · 64% over 11cacheWeakest map · 11% over 9
MapGradePlayedRecordWin rateAvg rating
mirageD226–1627%-0.05
nukeA1912–763%-0.02
ancientD185–1328%-0.04
infernoC135–838%-0.04
anubisA117–464%0.00
cacheD91–811%-0.02
dust2D62–433%-0.01
vertigo—10–10%-0.03
shelter—10–10%-0.07

Across the last 100 tracked matches.

Lifetime stats

21,204Lifetime kills
0.76K/D
1,778Matches
37.6%Match win rate
40.3%Headshot %
8.5%Shot accuracy
2,727MVPs
1,345Hours (in match)
773Bombs planted
213Bombs defused

Most-used weapons

Lifetime map wins

2,056nuke
1,348inferno
1,171lake
811dust2
377train
241vertigo
173italy
96office

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

Faceit stats

Combat

86Matches
48%Win rate
0.70Avg K/D
61.2ADR
39%Headshot %

Clutches & streaks

29%1v1 clutch win
16%1v2 clutch win
4Longest win streak

Recent Faceit resultsWWLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage2843%0.6611.3
Nuke1958%0.8913.3
Anubis1471%0.659.4
Ancient1346%0.7211.6
Inferno633%0.5710.3
Train30%0.368.3
Dust230%0.6413.3

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.

15.4%Headshot accuracy
37.3%Accuracy (enemy spotted)
38.3%Spray accuracy
76.4%Counter-strafing
9.2°Preaim
600msReaction time
77.2%T opening success
46.5%CT opening success
0.33Enemies flashed / flash
3.2%Flash assists
7.07HE damage / grenade
2.21Flashes / 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. 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 0.3325 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Cache

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

11% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
mirage5–13-0.0214%3 Nov →
inferno5–13-0.0511%1 Nov →
nuke13–10-0.039%1 Nov →
ancient9–13-0.0418%1 Nov →
nuke13–110.0621%1 Nov →
anubis6–13-0.0310%29 Oct →
dust215–15-0.0110%27 Oct →
dust213–70.0417%27 Oct →
ancient13–110.0313%24 Oct →
cache9–130.0219%23 Oct →
dust28–13-0.0616%23 Oct →
dust29–130.0713%23 Oct →
dust20–4-0.060%23 Oct →
ancient13–10-0.0213%22 Oct →
nuke13–20.0511%18 Oct →
nuke15–15-0.0117%17 Oct →
mirage7–13-0.0618%17 Oct →
ancient4–13-0.0210%15 Oct →
mirage4–13-0.0326%14 Oct →
cache6–130.1020%12 Oct →
inferno4–13-0.104%12 Oct →
cache2–13-0.0813%12 Oct →
nuke6–13-0.0516%11 Oct →
anubis13–40.0913%9 Oct →
ancient9–130.0215%9 Oct →
mirage13–11-0.0420%7 Oct →
nuke13–100.029%4 Oct →
inferno13–7-0.0317%4 Oct →
mirage3–13-0.0128%4 Oct →
mirage13–8-0.0531%3 Oct →
inferno10–13-0.088%2 Oct →
vertigo11–13-0.0314%29 Sept →
ancient13–11-0.049%27 Sept →
mirage8–13-0.0310%27 Sept →
anubis13–30.0436%27 Sept →
inferno7–13-0.0525%27 Sept →
ancient10–13-0.005%26 Sept →
mirage13–3-0.0217%25 Sept →
inferno8–130.0417%25 Sept →
inferno13–8-0.0413%24 Sept →
anubis13–6-0.0320%23 Sept →
ancient4–13-0.0729%20 Sept →
cache7–13-0.018%20 Sept →
nuke9–13-0.0521%20 Sept →
nuke13–5-0.068%18 Sept →
ancient14–16-0.0610%18 Sept →
cache8–13-0.0311%16 Sept →
mirage11–13-0.019%16 Sept →
ancient16–14-0.0217%15 Sept →
inferno13–16-0.0411%12 Sept →
cache11–13-0.0417%12 Sept →
inferno7–10.040%12 Sept →
anubis13–60.023%12 Sept →
dust213–9-0.0215%12 Sept →
nuke13–11-0.0011%12 Sept →
nuke3–13-0.067%12 Sept →
ancient2–13-0.099%12 Sept →
anubis12–16-0.0611%11 Sept →
anubis9–40.0713%10 Sept →
cache6–13-0.076%8 Sept →
mirage5–13-0.0910%6 Sept →
ancient10–13-0.0312%6 Sept →
mirage15–15-0.018%6 Sept →
cache16–13-0.0211%5 Sept →
mirage16–14-0.0317%5 Sept →
nuke13–5-0.0224%5 Sept →
anubis6–13-0.0922%5 Sept →
ancient10–13-0.0913%4 Sept →
mirage3–13-0.0711%4 Sept →
inferno4–13-0.134%4 Sept →
shelter9–13-0.0719%4 Sept →
anubis13–60.0210%4 Sept →
ancient13–16-0.027%3 Sept →
nuke13–8-0.0213%3 Sept →
mirage2–13-0.0012%3 Sept →
inferno13–6-0.0233%2 Sept →
anubis13–70.0117%2 Sept →
ancient11–130.0011%2 Sept →
mirage13–90.0431%1 Sept →
nuke13–9-0.087%1 Sept →
inferno13–8-0.0124%31 Aug →
ancient13–8-0.0319%30 Aug →
mirage7–13-0.0918%29 Aug →
nuke13–10-0.0211%29 Aug →
cache14–16-0.0716%28 Aug →
ancient6–13-0.0620%28 Aug →
anubis9–13-0.0322%28 Aug →
inferno8–13-0.0510%27 Aug →
nuke8–13-0.0521%27 Aug →
nuke4–13-0.0018%27 Aug →
mirage9–7-0.0231%27 Aug →
mirage11–13-0.0919%26 Aug →
ancient1–13-0.135%23 Aug →
mirage0–13-0.1211%21 Aug →
nuke8–5-0.0517%21 Aug →
mirage4–13-0.0426%21 Aug →
mirage11–13-0.1311%21 Aug →
nuke2–13-0.0421%21 Aug →
nuke13–8-0.007%18 Aug →
mirage5–13-0.0615%15 Aug →

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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