Siah1

Siah1 — CS2 Stats

US76561198054031356[U:1:93765628]Steam profile ↗✓ No bans

1,318Tracked matches52%Win rate2022Tracked since
CSDB Rating5.4 DevelopingAll-Rounder
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGSiah1FACEITLevel 2STANDINGTop 97.9% of rankedcsdb.gg/stats

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Performance scores

Aim67
Positioning45
Utility42

0–100 skill scores via Leetify.

Recent form

COLD43–44–13Last 10043%Win rateLLLLLLTTWL

Last 10 vs previous 10: −50pp win rate · −0.03 avg rating · −3.1pp headshot accuracy · −4ms reaction

Win rate down 50pp 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

  • 0–5 · 0% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 20%
  • Avg reaction 617ms

Last 10

  • 1–7–2 · 10% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 17%
  • Avg reaction 610ms

Last 20

  • 7–9–4 · 35% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 19%
  • Avg reaction 613ms

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.

Aim6.7
Utility4.2
Positioning4.5
Opening Duels3.2

Strong CT-side opener

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

NiKo

Plays most like NiKo 95% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower positioning profile; 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

T-side openings. Opening success drops from 53% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 625ms 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

Aim6.7
Positioning4.5
Utility4.2
Mechanics6.9
Opening Duels2.8
Win Impact5.7

Composite 5.4/10 (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 rating-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time622ms−48ms
first ⅓ avg 670ms → last ⅓ avg 622ms
Headshot accuracy17.4%+1.4%
first ⅓ avg 16.0% → last ⅓ avg 17.4%

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

0.17Best match rating · 13–9 · anubis, 2 Jul →
33%Best headshot accuracy · 13–9 · vertigo, 25 Aug →
422msFastest reaction time · 2–13 · inferno, 6 Sept →
13–2Biggest win · ancient, 10 Aug →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L6Current streak
4–6In matches decided by ≤2 rounds
2Overtime games

Map breakdown

vertigoBest map · 63% over 8ancientWeakest map · 27% over 11
MapGradePlayedRecordWin rateAvg rating
mirageD144–1029%-0.00
nukeB147–750%-0.02
cacheB137–654%-0.01
dust2C114–736%0.00
ancientD113–827%-0.01
infernoB115–645%-0.03
anubisC94–544%0.00
vertigoA85–363%-0.01
trainC52–340%0.01
overpass—42–250%-0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

94Matches
45%Win rate
1.08Avg K/D
—ADR
27%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
5Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno10%1.0019.0
Vertigo10%0.672.0

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.

17.9%Headshot accuracy
33.4%Accuracy (enemy spotted)
31.8%Spray accuracy
81.2%Counter-strafing
7.9°Preaim
625msReaction time
26.1%T opening success
52.5%CT opening success
0.70Enemies flashed / flash
2.9%Flash assists
5.17HE damage / grenade
5.12Flashes / 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

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 26.0663% — below the 40% mark we flag

Spend your practice time on Ancient

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.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust211–130.0425%18 Sept →
ancient11–13-0.0211%10 Sept →
train3–13-0.0324%10 Sept →
mirage3–13-0.0722%8 Sept →
anubis0–13-0.0918%8 Sept →
ancient10–13-0.0310%8 Sept →
train12–12-0.0219%7 Sept →
cache12–12-0.0615%7 Sept →
nuke13–10-0.0522%6 Sept →
inferno2–13-0.097%6 Sept →
cache13–8-0.079%31 Aug →
inferno8–13-0.0514%31 Aug →
mirage12–12-0.0716%26 Aug →
train13–9-0.0032%25 Aug →
vertigo13–90.0033%25 Aug →
inferno13–11-0.0311%25 Aug →
mirage13–50.0624%24 Aug →
vertigo11–13-0.0221%24 Aug →
nuke13–90.0222%24 Aug →
overpass12–120.0122%18 Aug →
vertigo13–90.0117%14 Aug →
dust26–130.0118%14 Aug →
nuke4–13-0.0513%12 Aug →
nuke13–4-0.019%11 Aug →
dust213–100.0018%10 Aug →
train13–70.0826%10 Aug →
ancient13–20.0214%10 Aug →
ancient4–130.0218%9 Aug →
cache13–11-0.0215%7 Aug →
inferno12–120.029%7 Aug →
ancient5–130.0415%1 Aug →
anubis12–120.0110%1 Aug →
mirage13–100.0215%30 Jul →
inferno13–2-0.0113%30 Jul →
inferno16–13-0.0510%29 Jul →
ancient3–13-0.075%22 Jul →
anubis13–10-0.0111%22 Jul →
anubis3–13-0.0614%22 Jul →
dust213–9-0.0211%22 Jul →
train9–130.0513%21 Jul →
cache12–16-0.0125%21 Jul →
nuke12–12-0.0415%20 Jul →
mirage12–12-0.0116%20 Jul →
nuke10–13-0.0623%15 Jul →
inferno10–13-0.0118%15 Jul →
mirage10–13-0.0514%15 Jul →
cache8–13-0.0316%15 Jul →
nuke13–9-0.0111%14 Jul →
ancient7–13-0.0519%14 Jul →
anubis13–40.1317%13 Jul →
overpass13–5-0.0217%8 Jul →
vertigo13–80.0119%8 Jul →
ancient13–40.067%8 Jul →
mirage2–130.0614%8 Jul →
dust213–50.069%8 Jul →
dust211–13-0.0210%7 Jul →
cache9–13-0.0221%7 Jul →
inferno13–7-0.066%7 Jul →
mirage2–130.0026%6 Jul →
vertigo13–10-0.0418%6 Jul →
mirage0–9-0.0013%6 Jul →
dust25–130.0419%6 Jul →
cache10–13-0.0617%5 Jul →
inferno13–9-0.039%3 Jul →
nuke13–7-0.0616%3 Jul →
anubis4–13-0.0617%3 Jul →
mirage9–130.0112%2 Jul →
vertigo13–40.0112%2 Jul →
anubis13–90.1715%2 Jul →
nuke6–13-0.0422%1 Jul →
mirage8–13-0.019%30 Jun →
ancient11–13-0.023%30 Jun →
vertigo9–13-0.0121%24 Jun →
overpass12–120.009%19 Jun →
inferno12–12-0.0517%19 Jun →
mirage13–7-0.0318%19 Jun →
cache13–110.0211%18 Jun →
anubis8–13-0.0519%18 Jun →
overpass9–0-0.029%18 Jun →
mirage6–13-0.0021%18 Jun →
nuke11–130.0512%18 Jun →
mirage13–80.0625%10 Jun →
ancient13–10-0.0016%10 Jun →
nuke13–90.0621%9 Jun →
cache3–90.0115%7 Jun →
dust213–10-0.0321%7 Jun →
inferno5–13-0.0117%5 Jun →
cache13–6-0.0021%4 Jun →
nuke10–13-0.0019%4 Jun →
anubis13–11-0.0422%4 Jun →
vertigo12–12-0.0310%3 Jun →
cache13–70.0112%3 Jun →
nuke5–13-0.0217%3 Jun →
dust210–13-0.0020%29 May →
cache13–50.0417%28 May →
dust210–13-0.0513%27 May →
dust212–12-0.0118%26 May →
nuke9–1-0.0413%26 May →
ancient12–12-0.0117%26 May →
cache13–30.0417%26 May →

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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