KQLY

KQLY — CS2 Stats

SE76561199066935110[U:1:1106669382]Steam profile ↗✓ No bans

1,118Tracked matches57%Win rate2020Tracked since
CSDB Rating6.1 SolidPositional Player
FaceitLevel 3Top 90.6% of ranked FACEIT players
WingmanGold Nova II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Sep 2026 (50 days ago). Ranks are recorded once per day this page is viewed.

+61Tracked matches · now 1,118
+6.7ppWin rate · 50.0% → 56.7%

Rating over time

26Days played since 2026-08-13

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

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CSDB.GGKQLYFACEITLevel 3STANDINGTop 90.6% of rankedcsdb.gg/stats

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Performance scores

Aim80
Positioning57
Utility35

0–100 skill scores via Leetify.

Recent form

STEADY49–51Last 10049%Win rateLWLLWLLLWW

Last 10 vs previous 10: −40pp win rate · −0.03 avg rating · −5.8pp headshot accuracy · +88ms reaction

Win rate down 40pp 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 15%
  • Avg reaction 581ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 17%
  • Avg reaction 549ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 19%
  • Avg reaction 506ms

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 (+1.1 against its own average).

Aim8.0
Utility3.5
Positioning5.7
Opening Duels4.6

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 89% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower positioning 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. 64% 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.

Counter-strafing. Only 68% 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

Aim8.0
Positioning5.7
Utility3.5
Mechanics4.0
Opening Duels6.8
Win Impact7.2

Composite 6.1/10 (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 rating0.02+0.02
first ⅓ avg -0.00 → last ⅓ avg 0.02
Reaction time501ms−27ms
first ⅓ avg 528ms → last ⅓ avg 501ms
Headshot accuracy18.2%+3.1%
first ⅓ avg 15.2% → last ⅓ avg 18.2%

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

0.16Best match rating · 13–3 · dust2, 19 Aug →
46%Best headshot accuracy · 13–9 · dust2, 23 Sept →
344msFastest reaction time · 11–13 · inferno, 28 Aug →
13–1Biggest win · anubis, 11 Oct →

Across the last 100 tracked matches.

Highlights

7Longest win streak
10–10In matches decided by ≤2 rounds
13Overtime games

Map breakdown

cacheBest map · 60% over 10nukeWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
mirageB2210–1245%-0.01
dust2C166–1038%0.01
infernoB137–654%0.02
anubisB126–650%0.02
vertigoB105–550%0.02
cacheA106–460%0.02
ancientB63–350%-0.01
nukeD51–420%-0.01
overpass—43–175%0.02
train—22–0100%-0.04

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Nuke 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
36.0%Accuracy (enemy spotted)
38.1%Spray accuracy
67.8%Counter-strafing
7.2°Preaim
486msReaction time
63.7%T opening success
50.5%CT opening success
0.59Enemies flashed / flash
7.2%Flash assists
2.75HE damage / grenade
3.85Flashes / 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

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.8523 — below the 4 mark we flag

    Grenade Lineups →
Spend your practice time on Nuke

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust26–13-0.0519%19 Oct →
ancient13–80.0019%18 Oct →
vertigo9–130.0712%18 Oct →
mirage6–13-0.0710%18 Oct →
vertigo13–70.0714%18 Oct →
dust211–13-0.048%16 Oct →
anubis8–13-0.0216%15 Oct →
inferno7–130.0133%15 Oct →
cache13–110.0423%15 Oct →
overpass19–160.0111%12 Oct →
ancient8–13-0.0624%12 Oct →
mirage19–17-0.0418%12 Oct →
anubis13–20.1038%12 Oct →
vertigo13–11-0.0122%12 Oct →
mirage13–90.0227%12 Oct →
ancient13–7-0.0510%11 Oct →
cache7–130.0414%11 Oct →
inferno13–100.0522%11 Oct →
anubis13–10.1224%11 Oct →
anubis13–110.1524%11 Oct →
inferno13–7-0.029%11 Oct →
inferno9–13-0.0717%11 Oct →
vertigo11–13-0.0417%11 Oct →
dust211–13-0.0111%11 Oct →
mirage3–130.0221%11 Oct →
inferno13–90.0421%2 Oct →
mirage13–100.0213%2 Oct →
dust210–130.0421%2 Oct →
inferno13–70.0726%2 Oct →
overpass16–130.1413%2 Oct →
mirage8–130.0217%2 Oct →
vertigo7–13-0.0015%26 Sept →
inferno19–22-0.0111%26 Sept →
nuke11–130.0222%25 Sept →
dust21–11-0.0123%25 Sept →
dust222–190.0430%24 Sept →
mirage13–90.0019%24 Sept →
vertigo13–80.0114%23 Sept →
cache13–50.0325%23 Sept →
mirage13–11-0.0214%23 Sept →
inferno13–60.0733%23 Sept →
dust213–9-0.0446%23 Sept →
anubis6–13-0.0418%22 Sept →
vertigo13–90.0722%22 Sept →
inferno11–30.1427%22 Sept →
cache13–3-0.016%14 Sept →
inferno11–13-0.0314%11 Sept →
nuke11–13-0.0510%5 Sept →
overpass13–8-0.028%5 Sept →
mirage8–130.0415%5 Sept →
dust211–13-0.0111%5 Sept →
inferno8–13-0.0616%5 Sept →
dust213–10-0.0138%5 Sept →
mirage16–120.0217%4 Sept →
ancient13–110.099%4 Sept →
dust29–13-0.0018%4 Sept →
cache8–130.0418%4 Sept →
cache16–190.0211%4 Sept →
mirage6–13-0.053%3 Sept →
ancient5–13-0.0511%3 Sept →
anubis16–140.0630%31 Aug →
cache13–80.0117%31 Aug →
anubis4–13-0.014%31 Aug →
anubis13–90.0010%31 Aug →
inferno11–130.0317%28 Aug →
nuke13–9-0.044%28 Aug →
dust29–13-0.0123%26 Aug →
mirage13–10-0.056%26 Aug →
mirage16–120.0317%26 Aug →
ancient9–130.0211%25 Aug →
dust213–5-0.0022%25 Aug →
train16–14-0.0119%25 Aug →
dust213–16-0.0421%25 Aug →
mirage4–130.0219%25 Aug →
vertigo13–90.0621%25 Aug →
inferno22–200.0114%23 Aug →
anubis2–11-0.065%19 Aug →
mirage11–13-0.0412%19 Aug →
cache7–13-0.0914%19 Aug →
train13–11-0.068%19 Aug →
dust213–30.1613%19 Aug →
mirage13–70.017%19 Aug →
dust27–130.1029%19 Aug →
dust213–90.0815%19 Aug →
mirage10–13-0.0614%19 Aug →
nuke4–13-0.0023%18 Aug →
anubis9–13-0.0411%18 Aug →
mirage13–8-0.0417%18 Aug →
vertigo10–130.0417%18 Aug →
vertigo10–13-0.0811%18 Aug →
cache13–40.0820%18 Aug →
mirage8–13-0.0313%18 Aug →
cache13–60.007%18 Aug →
mirage10–130.0314%18 Aug →
overpass4–13-0.0724%18 Aug →
anubis8–130.0112%18 Aug →
nuke20–220.0123%14 Aug →
mirage8–13-0.0119%14 Aug →
anubis13–10-0.0410%13 Aug →
mirage4–13-0.0511%13 Aug →

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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