Aqolle

Aqolle — CS2 Stats

US76561198098596791[U:1:138331063]Steam profile ↗✓ No bans

1,642Tracked matches37%Win rate2020Tracked since
2,396Hours in CS9Hrs last 2 wks
CSDB Rating5.7 SolidPositional Player
Premier CS Rating12,855Blue band · top ~39.8% of ranked players (population est.)
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 6 Sep 2026 (52 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 12,855 → 12,855
+25Tracked matches · now 1,642
−13.0ppWin rate · 50.0% → 37.0%

Rating over time

Premier CS Rating: 12,855 +2 24 Jul – 6 Sept · 8 days played
12,78213,229peak 13,22924 Jul6 Sept
13,475Peak Premier in tracked matches
28Days played since 2026-07-23

Premier CS Rating

  • 374 below peak (13,229)
  • -260 over 30 days · steady
  • Next: Purple band at 15,000 — 2,145 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-08-29
  • Light Blue band first seen 2026-08-29

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 3 among CSDB-tracked players (n=10,505), 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 3 medianLevel 4 medianvs Level 4
Headshot rate41.6%41.8%42.7%1.2% short
Shot accuracy6.6%12.2%11.2%4.6% short
Kill/death ratio0.950.980.990.05 short
Match win rate48.7%43.3%43.9%above

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

Widest gap: Shot accuracy. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGAqolleFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER12,855 · Blue 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

Aim81
Positioning59
Utility49

0–100 skill scores via Leetify.

Recent form

COLD46–43–11Last 10046%Win rateLLWWWLLTLL

Last 10 vs previous 10: −20pp win rate · −0.00 avg rating · −2.7pp headshot accuracy · +3ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 624ms

Last 10

  • 3–6–1 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 597ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 595ms

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 (+2.1 against its own average).

Aim8.1
Utility4.9
Positioning5.9
Opening Duels4.3
Clutch0.0

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 97% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; 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. 589ms 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

Aim8.1
Positioning5.9
Utility4.9
Mechanics7.3
Opening Duels5.0
Win Impact0.7

Composite 5.7/10 (Solid), 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-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time596ms−75ms
first ⅓ avg 671ms → last ⅓ avg 596ms
Headshot accuracy17.5%−1.0%
first ⅓ avg 18.5% → last ⅓ avg 17.5%

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

0.15Best match rating · 13–4 · vertigo, 28 Jul →
44%Best headshot accuracy · 13–5 · vertigo, 9 Aug →
477msFastest reaction time · 12–12 · italy, 17 Oct →
13–1Biggest win · ancient, 2 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L2Current streak
6–5In matches decided by ≤2 rounds
2Overtime games

Map breakdown

ancientBest map · 78% over 9officeWeakest map · 25% over 8
MapGradePlayedRecordWin rateAvg rating
cacheC125–742%-0.02
infernoC125–742%-0.01
vertigoS118–373%0.02
nukeA116–555%0.01
mirageD113–827%-0.01
dust2C104–640%-0.02
ancientS97–278%-0.00
officeD82–625%-0.01
anubisB63–350%0.02
train—30–30%0.02
shelter—21–150%-0.01
fachwerk—21–150%-0.04
boulder—10–10%-0.09
italy—10–10%0.01
debris—11–0100%-0.07

Across the last 100 tracked matches.

Lifetime stats

57,418Lifetime kills
0.95K/D
4,004Matches
48.7%Match win rate · Top 25% of Level 3 players
41.6%Headshot %
6.6%Shot accuracy
6,531MVPs
1,383Hours (in match)
1,329Bombs planted
794Bombs defused

Most-used weapons

AK-4715,472
AWP6,150
SSG 083,686
MP92,436
P901,013

Lifetime map wins

6,105inferno
5,760dust2
4,851nuke
2,292vertigo
757train
506office
183italy
30cbble

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

Faceit stats

Combat

11Matches
27%Win rate
0.76Avg K/D
75.8ADR
51%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage40%0.6611.3
Inferno425%0.9515.3
Ancient250%0.548.5
Nuke1100%0.8511.0

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.

17.2%Headshot accuracy
37.6%Accuracy (enemy spotted)
39.3%Spray accuracy
82.6%Counter-strafing
7.8°Preaim
589msReaction time
49.4%T opening success
50.9%CT opening success
0.51Enemies flashed / flash
4.3%Flash assists
8.93HE damage / grenade
11.03Flashes / match

Recommended for you

Spend your practice time on Mirage

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

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
boulder7–13-0.0911%24 Oct →
train11–130.0010%24 Oct →
cache13–80.0617%24 Oct →
office13–100.0511%24 Oct →
inferno13–80.0323%24 Oct →
ancient6–13-0.0411%18 Oct →
vertigo6–13-0.0119%18 Oct →
italy12–120.0119%17 Oct →
inferno8–13-0.0512%17 Oct →
office1–13-0.1027%17 Oct →
dust213–70.0125%17 Oct →
nuke12–120.1118%17 Oct →
vertigo1–13-0.0517%30 Sept →
mirage13–8-0.0213%26 Sept →
inferno8–13-0.1116%26 Sept →
ancient5–13-0.0116%26 Sept →
vertigo13–10-0.0414%26 Sept →
office2–13-0.0436%19 Sept →
anubis13–70.0518%19 Sept →
nuke13–50.0117%19 Sept →
dust211–130.0315%13 Sept →
train12–120.0028%13 Sept →
nuke11–13-0.0116%13 Sept →
inferno2–13-0.0429%12 Sept →
vertigo10–130.0126%10 Sept →
vertigo13–80.1214%2 Sept →
ancient13–10.0411%2 Sept →
office10–130.009%2 Sept →
mirage10–13-0.0214%27 Aug →
inferno7–130.0514%27 Aug →
ancient13–11-0.0924%27 Aug →
cache13–11-0.0413%27 Aug →
nuke13–3-0.0117%26 Aug →
train5–130.0520%26 Aug →
dust27–13-0.0519%26 Aug →
vertigo13–60.0223%26 Aug →
cache13–6-0.0427%26 Aug →
cache12–120.0130%19 Aug →
anubis7–13-0.0631%19 Aug →
ancient13–100.0417%19 Aug →
inferno13–80.088%19 Aug →
nuke7–13-0.1224%19 Aug →
mirage8–13-0.0211%15 Aug →
anubis10–130.0111%15 Aug →
inferno13–100.0114%15 Aug →
cache13–6-0.015%15 Aug →
nuke12–12-0.0618%13 Aug →
office7–130.0018%9 Aug →
vertigo13–5-0.0444%9 Aug →
shelter13–80.0113%9 Aug →
fachwerk2–5-0.0625%9 Aug →
mirage6–130.0719%8 Aug →
mirage5–13-0.059%8 Aug →
office13–90.1116%8 Aug →
anubis8–13-0.0231%8 Aug →
inferno13–11-0.0110%8 Aug →
nuke13–20.1020%6 Aug →
dust213–5-0.1314%6 Aug →
cache12–12-0.046%6 Aug →
debris9–6-0.0710%5 Aug →
office4–13-0.0911%4 Aug →
inferno3–13-0.080%4 Aug →
nuke13–40.0227%4 Aug →
mirage12–12-0.0417%4 Aug →
anubis13–80.0511%4 Aug →
ancient13–8-0.0513%4 Aug →
vertigo13–90.0110%3 Aug →
cache12–12-0.0320%2 Aug →
inferno13–3-0.017%2 Aug →
mirage13–90.0722%2 Aug →
vertigo13–80.0111%2 Aug →
ancient13–20.1011%2 Aug →
dust26–130.0316%2 Aug →
shelter11–13-0.028%1 Aug →
vertigo13–110.0121%1 Aug →
fachwerk6–4-0.0240%1 Aug →
dust211–13-0.0214%1 Aug →
dust24–13-0.0925%29 Jul →
cache13–3-0.0622%29 Jul →
dust213–11-0.0313%29 Jul →
inferno8–13-0.0716%29 Jul →
mirage1–9-0.0443%28 Jul →
vertigo13–40.1517%28 Jul →
office12–120.0218%28 Jul →
nuke13–30.0411%28 Jul →
dust213–20.0331%28 Jul →
inferno8–80.039%28 Jul →
nuke15–150.0120%25 Jul →
mirage5–13-0.0426%25 Jul →
cache8–13-0.0313%24 Jul →
mirage9–13-0.0424%24 Jul →
ancient13–90.0016%24 Jul →
anubis13–30.086%24 Jul →
ancient13–4-0.0120%24 Jul →
cache10–130.0318%24 Jul →
nuke13–100.0515%24 Jul →
cache12–16-0.0622%23 Jul →
dust29–13-0.0115%23 Jul →
cache9–13-0.0115%23 Jul →
mirage13–70.0025%23 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 →

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