Akos

Akos — CS2 Stats

SE76561197961056207[U:1:790479]Steam profile ↗✓ No bans

165Tracked matches46%Win rate2020Tracked since
990Hours in CS
CSDB Rating4.9 DevelopingAll-Rounder
Ladder ranks via Leetify

Performance scores

Aim46
Positioning61
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY42–50–8Last 10042%Win rateTLWWWLLLWL

Last 10 vs previous 10: 0pp win rate · +0.06 avg rating · +2.7pp headshot accuracy · −27ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 3–1–1 · 60% win rate
  • Avg rating 0.08
  • Avg headshot accuracy 21%
  • Avg reaction 569ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 19%
  • Avg reaction 623ms

Last 20

  • 8–10–2 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 18%
  • Avg reaction 636ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim4.6
Utility4.5
Positioning6.1
Opening Duels6.0

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

donk

Plays most like donk 75% playstyle similarity

Most alike: utility contribution, positioning profile.

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

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

Aim4.6
Positioning6.1
Utility4.5
Mechanics5.4
Opening Duels4.5
Win Impact3.8

Composite 4.9/10 (Developing), 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 rating0.03−0.05
first ⅓ avg 0.09 → last ⅓ avg 0.03
Reaction time648ms−22ms
first ⅓ avg 670ms → last ⅓ avg 648ms
Headshot accuracy17.1%+2.3%
first ⅓ avg 14.8% → last ⅓ avg 17.1%

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 · 13–2 · inferno, 18 Jan →
44%Best headshot accuracy · 4–0 · nuke, 16 Aug →
414msFastest reaction time · 13–8 · inferno, 15 Aug →
13–0Biggest win · vertigo, 28 Mar →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

vertigoBest map · 64% over 14mirageWeakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
officeB2211–1150%0.05
nukeD165–1131%0.04
infernoC167–944%0.06
vertigoA149–564%0.07
mirageD103–730%0.10
cacheD62–433%0.04
train—41–325%0.06
overpass—31–233%0.02
anubis—20–20%0.06
dust2—21–150%0.11
ancient—21–150%-0.00
fachwerk—11–0100%0.03
stronghold—10–10%0.10
alpine—10–10%-0.04

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (30% over 10). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

50,855Lifetime kills
1.23K/D · Top 25% of tracked players
2,636Matches
49.4%Match win rate · Top 25% of tracked players
35.7%Headshot %
20.4%Shot accuracy · Top 5% of tracked players
5,816MVPs
990Hours (in match)
2,781Bombs planted
577Bombs defused

Most-used weapons

AK-4710,322
AWP4,896
P902,550
P2502,377
SSG 081,772
MAG-71,404

Lifetime map wins

5,087inferno
1,457lake
1,314dust2
1,194train
1,169nuke
1,037bank
690safehouse
636vertigo

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.

16.6%Headshot accuracy
33.4%Accuracy (enemy spotted)
37.4%Spray accuracy
74.4%Counter-strafing
12.7°Preaim
654msReaction time
44.7%T opening success
51.1%CT opening success
0.44Enemies flashed / flash
5.8%Flash assists
8.15HE damage / grenade
5.66Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.6962° — above the 12° 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 0.4403 — below the 0.5 mark we flag

    Grenade Lineups →
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.

30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
office12–120.129%22 Aug →
nuke4–13-0.0224%16 Aug →
nuke4–00.0944%16 Aug →
vertigo13–30.119%16 Aug →
inferno13–80.0918%15 Aug →
office10–130.0717%14 Aug →
inferno3–130.0023%12 Aug →
vertigo3–130.0521%7 Aug →
cache16–13-0.0412%26 Jul →
cache1–130.0616%22 Jul →
nuke16–12-0.0120%22 Jul →
vertigo3–13-0.0425%19 Jul →
office5–13-0.0416%19 Jul →
inferno2–13-0.0211%18 Jul →
overpass6–13-0.062%18 Jul →
office13–6-0.0217%9 Jul →
fachwerk13–100.0318%9 Jul →
office12–120.0920%3 Jul →
cache2–13-0.0527%26 Jun →
vertigo13–100.0110%25 Jun →
inferno7–130.0313%25 Jun →
office5–13-0.0115%6 May →
nuke13–100.1212%6 May →
cache13–30.1329%6 May →
cache10–130.0621%29 Apr →
cache7–130.1018%29 Apr →
office13–30.1010%26 Apr →
vertigo13–60.0514%26 Apr →
office13–90.0822%26 Apr →
inferno5–130.0313%26 Apr →
train4–13-0.0413%25 Apr →
office9–13-0.0113%19 Apr →
nuke4–130.0713%5 Apr →
office6–130.0410%5 Apr →
anubis7–130.0514%5 Apr →
office11–13-0.008%4 Apr →
nuke8–130.0412%3 Apr →
office13–50.0915%31 Mar →
inferno6–130.034%31 Mar →
inferno13–60.0614%30 Mar →
nuke12–12-0.017%30 Mar →
office13–100.0413%28 Mar →
mirage9–130.0615%28 Mar →
vertigo13–00.0333%28 Mar →
office12–120.089%28 Mar →
vertigo8–130.0625%28 Mar →
inferno8–13-0.0216%27 Mar →
nuke10–130.0812%27 Mar →
office13–100.0214%26 Mar →
mirage6–130.1018%26 Mar →
vertigo13–90.1717%25 Mar →
nuke12–120.0916%23 Mar →
office13–40.0316%22 Mar →
inferno4–13-0.0513%22 Mar →
nuke5–130.0113%22 Mar →
nuke16–140.0513%22 Mar →
mirage7–13-0.039%21 Mar →
inferno9–130.0324%21 Mar →
nuke6–130.0317%14 Mar →
office13–100.0218%14 Mar →
mirage7–130.109%13 Mar →
overpass6–130.0214%13 Mar →
vertigo3–130.0120%13 Mar →
train11–130.0312%13 Mar →
mirage13–60.1522%13 Mar →
office13–40.157%13 Mar →
nuke5–130.0115%13 Mar →
inferno13–40.0317%13 Mar →
vertigo13–40.0515%13 Mar →
nuke6–130.0427%6 Mar →
mirage13–100.0918%6 Mar →
train12–120.0716%25 Feb →
mirage13–80.1520%25 Feb →
nuke5–13-0.0314%31 Jan →
vertigo13–90.049%31 Jan →
dust26–130.0613%31 Jan →
vertigo13–20.1617%28 Jan →
train13–40.1920%28 Jan →
office13–30.0511%25 Jan →
inferno13–20.0922%25 Jan →
mirage12–120.1813%25 Jan →
vertigo9–130.034%24 Jan →
mirage12–120.138%24 Jan →
ancient13–4-0.035%23 Jan →
dust213–50.1724%23 Jan →
anubis9–130.069%23 Jan →
office13–90.1015%23 Jan →
stronghold6–130.1014%23 Jan →
office8–130.0613%23 Jan →
inferno13–110.1314%23 Jan →
vertigo13–50.1915%23 Jan →
alpine4–13-0.048%22 Jan →
inferno6–130.1519%21 Jan →
ancient3–130.027%21 Jan →
mirage7–130.0725%21 Jan →
nuke13–10-0.017%18 Jan →
inferno13–20.2217%18 Jan →
overpass13–110.1018%17 Jan →
office7–130.1117%16 Jan →
inferno13–50.1522%15 Jan →

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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