Ayce_

Ayce_ — CS2 Stats

CH76561199094135330[U:1:1133869602]Steam profile ↗✓ No bans

284Tracked matches57%Win rate2021Tracked since
CSDB Rating6.2 SolidPositional Player
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 17 Sep 2026 (45 days ago). Ranks are recorded once per day this page is viewed.

+24Tracked matches · now 284
+8.4ppWin rate · 48.3% → 56.7%

Rating over time

37Days played since 2025-12-23

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

Performance scores

Aim73
Positioning58
Utility33

0–100 skill scores via Leetify.

Recent form

HOT44–52–4Last 10044%Win rateWLWWWLWWWW

Last 10 vs previous 10: +40pp win rate · +0.01 avg rating · −1.2pp headshot accuracy · −24ms reaction

Win rate up 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

  • 4–1 · 80% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 18%
  • Avg reaction 600ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 22%
  • Avg reaction 650ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • Avg reaction 662ms

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 (+1.7 against its own average).

Aim7.3
Utility3.3
Positioning5.8
Opening Duels3.2

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 91% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; 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. 654ms 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

Aim7.3
Positioning5.8
Utility3.3
Mechanics7.9
Opening Duels4.6
Win Impact7.2

Composite 6.2/10 (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 rating0.00+0.01
first ⅓ avg -0.01 → last ⅓ avg 0.00
Reaction time649ms−71ms
first ⅓ avg 719ms → last ⅓ avg 649ms
Headshot accuracy20.5%+6.4%
first ⅓ avg 14.1% → last ⅓ avg 20.5%

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

0.19Best match rating · 4–5 · train, 16 Feb →
40%Best headshot accuracy · 13–8 · inferno, 22 Oct →
516msFastest reaction time · 13–7 · inferno, 1 Nov →
13–1Biggest win · mirage, 17 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
3–7In matches decided by ≤2 rounds
6Overtime games

Map breakdown

ancientBest map · 67% over 9overpassWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
infernoD196–1332%-0.01
nukeC198–1142%0.01
mirageA169–756%0.00
dust2B136–746%-0.01
ancientS96–367%-0.01
trainD62–433%-0.00
vertigoC52–340%-0.03
overpassD51–420%0.01
anubis—43–175%-0.02
cache—31–233%-0.00
office—10–10%-0.03

Across the last 100 tracked matches.

Overpass is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Overpass 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.

20.5%Headshot accuracy
35.5%Accuracy (enemy spotted)
36.8%Spray accuracy
85.6%Counter-strafing
9.7°Preaim
654msReaction time
49.7%T opening success
46.9%CT opening success
0.39Enemies flashed / flash
1.4%Flash assists
6.77HE damage / grenade
4.31Flashes / 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 0.3859 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Overpass

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.

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–7-0.0319%1 Nov →
inferno5–130.0423%30 Oct →
dust213–20.0616%30 Oct →
mirage13–10-0.046%30 Oct →
train13–30.0425%30 Oct →
nuke8–130.0325%30 Oct →
vertigo13–4-0.0120%30 Oct →
ancient13–6-0.0519%22 Oct →
nuke13–90.1130%22 Oct →
inferno13–80.0340%22 Oct →
cache3–130.0229%22 Oct →
mirage13–10.0826%17 Oct →
nuke13–90.0028%17 Oct →
nuke13–9-0.0117%17 Oct →
nuke14–160.0023%2 Oct →
ancient1–13-0.0711%2 Oct →
mirage13–20.0535%1 Oct →
nuke11–130.0326%1 Oct →
ancient7–13-0.0216%1 Oct →
nuke13–160.0223%22 Sept →
train7–13-0.1135%19 Sept →
anubis13–9-0.1018%18 Sept →
mirage7–13-0.0429%18 Sept →
inferno10–130.0316%18 Sept →
mirage13–6-0.008%10 Sept →
nuke13–80.1015%10 Sept →
anubis13–90.019%10 Sept →
cache3–13-0.069%10 Sept →
nuke7–13-0.0310%2 Sept →
inferno13–10-0.0714%2 Sept →
dust25–13-0.0132%2 Sept →
inferno14–16-0.0118%2 Sept →
overpass12–120.0510%1 Sept →
vertigo10–13-0.0215%1 Sept →
ancient16–130.0614%1 Sept →
dust213–60.0413%29 Aug →
nuke13–50.0318%28 Aug →
vertigo4–130.0318%28 Aug →
mirage9–13-0.0218%28 Aug →
dust27–13-0.0723%28 Aug →
cache13–30.0418%22 Aug →
inferno13–60.0724%19 Apr →
inferno11–13-0.0222%19 Apr →
mirage8–13-0.019%19 Apr →
inferno9–13-0.0814%19 Apr →
mirage13–6-0.0712%10 Apr →
inferno5–13-0.057%10 Apr →
anubis13–60.0625%10 Apr →
ancient16–13-0.0513%10 Apr →
ancient13–100.0019%3 Apr →
overpass9–13-0.007%27 Mar →
overpass7–13-0.0320%27 Mar →
inferno3–13-0.066%27 Mar →
dust22–00.120%27 Mar →
mirage9–130.0214%27 Mar →
dust213–9-0.0211%25 Mar →
mirage9–130.0416%25 Mar →
inferno13–60.039%19 Mar →
inferno1–13-0.0519%19 Mar →
anubis1–13-0.0313%19 Mar →
ancient8–13-0.058%19 Mar →
inferno5–13-0.0228%19 Mar →
mirage13–10-0.0417%12 Mar →
overpass13–100.0319%12 Mar →
nuke3–130.0033%9 Mar →
mirage13–110.0513%9 Mar →
nuke13–70.0816%9 Mar →
inferno9–130.0212%9 Mar →
nuke5–13-0.079%9 Mar →
ancient13–60.0613%6 Mar →
ancient13–40.0517%21 Feb →
mirage13–20.1219%21 Feb →
nuke13–80.0310%21 Feb →
dust212–12-0.0118%20 Feb →
dust213–10.0311%20 Feb →
overpass12–120.024%20 Feb →
mirage2–130.0113%20 Feb →
dust23–13-0.0523%20 Feb →
train10–130.0418%20 Feb →
office8–13-0.0313%20 Feb →
train4–50.1916%16 Feb →
nuke8–13-0.0417%16 Feb →
inferno12–12-0.0220%16 Feb →
nuke14–16-0.0118%31 Jan →
inferno5–13-0.0614%31 Jan →
inferno13–20.1515%30 Jan →
inferno11–13-0.057%29 Jan →
mirage13–6-0.018%29 Jan →
nuke3–13-0.048%28 Jan →
vertigo13–10-0.0426%18 Jan →
dust20–11-0.050%15 Jan →
mirage9–13-0.0719%15 Jan →
train6–13-0.089%15 Jan →
vertigo2–8-0.110%12 Jan →
nuke6–13-0.097%12 Jan →
dust27–13-0.0917%12 Jan →
train2–3-0.0925%10 Jan →
dust213–70.0724%24 Dec →
nuke13–70.0311%24 Dec →
dust20–13-0.1224%23 Dec →

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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