Alicja

Alicja — CS2 Stats

76561198046054766[U:1:85789038]Steam profile ↗✓ No bans

1,804Tracked matches46%Win rate2020Tracked since
CSDB Rating5.3 DevelopingSupport
Premier CS Rating22,909Pink band · top ~5.3% of ranked players (population est.)
FaceitLevel 8Top 31.2% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

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CSDB.GGAlicjaFACEITLevel 8STANDINGTop 31.2% of rankedPREMIER22,909 · Pink bandcsdb.gg/stats

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Performance scores

Aim64
Positioning44
Utility66

0–100 skill scores via Leetify.

Recent form

COLD46–50–4Last 10046%Win rateLWWLLLLLWL

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · +3.4pp headshot accuracy · +51ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 19%
  • Avg reaction 589ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 588ms

Last 20

  • 6–13–1 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 16%
  • Avg reaction 563ms

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: Support — Utility contribution stands above the rest of this profile (+2.2 against its own average).

Aim6.4
Utility6.6
Positioning4.4
Opening Duels1.2
Clutch5.6

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 79% 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. 556ms 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

Aim6.4
Positioning4.4
Utility6.6
Mechanics4.6
Opening Duels2.9
Win Impact3.8

Composite 5.3/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time559ms−5ms
first ⅓ avg 564ms → last ⅓ avg 559ms
Headshot accuracy14.2%−3.1%
first ⅓ avg 17.4% → last ⅓ avg 14.2%

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

0.07Best match rating · 9–6 · inferno, 17 Sept →
67%Best headshot accuracy · 2–11 · cache, 10 Sept →
406msFastest reaction time · 12–12 · inferno, 15 Oct →
13–2Biggest win · cache, 23 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak
10–3In matches decided by ≤2 rounds
10Overtime games

Map breakdown

cacheBest map · 54% over 24infernoWeakest map · 37% over 19
MapGradePlayedRecordWin rateAvg rating
cacheB2413–1154%-0.03
infernoC197–1237%-0.05
anubisC156–940%-0.01
mirageC146–843%-0.02
nukeB126–650%-0.02
vertigoC52–340%-0.00
train—42–250%-0.02
overpass—32–167%-0.01
dust2—32–167%-0.01
ancient—10–10%-0.08

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (37% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

420Matches
53%Win rate
0.95Avg K/D
75.6ADR
43%Headshot %

Clutches & streaks

48%1v1 clutch win
17%1v2 clutch win
10Longest win streak

Recent Faceit resultsLWLWW

MapMatchesWin rateAvg K/DAvg kills
Anubis6050%0.8813.4
Inferno5860%1.0213.1
Mirage4854%0.9414.1
Cache3956%0.9914.0
Nuke3165%1.1015.0
Ancient2446%0.7412.6
Overpass1953%1.0514.7
Dust21436%0.9214.7

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.

14.6%Headshot accuracy
36.1%Accuracy (enemy spotted)
42.7%Spray accuracy
70.9%Counter-strafing
11.2°Preaim
556msReaction time
49.0%T opening success
34.0%CT opening success
0.68Enemies flashed / flash
16.3%Flash assists
13.40HE damage / grenade
6.08Flashes / 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. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 14.5689% — below the 15% mark we flag

    Aim Training →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 33.9702% — below the 40% mark we flag

Spend your practice time on Inferno

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

37% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache4–13-0.0411%11 Nov →
inferno13–100.0318%11 Nov →
vertigo13–3-0.0329%11 Nov →
anubis7–13-0.0620%11 Nov →
anubis10–130.0117%11 Nov →
cache9–13-0.0129%10 Nov →
inferno10–13-0.0617%10 Nov →
vertigo2–13-0.058%5 Nov →
cache13–11-0.0614%5 Nov →
inferno2–13-0.0710%5 Nov →
train6–13-0.0313%5 Nov →
inferno8–13-0.068%30 Oct →
train13–110.0322%30 Oct →
mirage9–130.0416%30 Oct →
nuke3–13-0.0314%30 Oct →
cache2–13-0.103%30 Oct →
inferno6–13-0.0321%23 Oct →
cache13–8-0.0314%22 Oct →
cache13–11-0.0616%22 Oct →
vertigo12–120.0512%18 Oct →
mirage13–8-0.0116%18 Oct →
overpass13–10-0.047%15 Oct →
mirage4–13-0.048%15 Oct →
inferno12–12-0.0516%15 Oct →
nuke13–80.0113%13 Oct →
cache13–70.0320%13 Oct →
train13–9-0.0311%7 Oct →
dust213–10-0.0015%7 Oct →
mirage6–13-0.059%7 Oct →
dust216–14-0.019%7 Oct →
cache13–5-0.0211%1 Oct →
cache8–13-0.0221%1 Oct →
mirage13–11-0.084%26 Sept →
vertigo13–100.0511%24 Sept →
nuke12–12-0.0118%23 Sept →
cache13–2-0.0730%23 Sept →
train0–13-0.058%23 Sept →
inferno5–13-0.074%23 Sept →
vertigo1–13-0.0513%23 Sept →
anubis13–90.0713%20 Sept →
overpass9–5-0.0416%20 Sept →
mirage7–13-0.0527%20 Sept →
mirage13–10-0.0018%20 Sept →
inferno6–9-0.0312%20 Sept →
inferno3–9-0.0116%20 Sept →
anubis4–13-0.0337%20 Sept →
mirage17–19-0.0518%19 Sept →
anubis13–100.0219%19 Sept →
cache13–80.0022%18 Sept →
anubis6–13-0.048%18 Sept →
inferno0–9-0.1223%17 Sept →
inferno9–60.0726%17 Sept →
anubis4–13-0.0016%17 Sept →
anubis3–13-0.022%17 Sept →
anubis3–13-0.0614%17 Sept →
nuke8–13-0.0815%17 Sept →
nuke8–13-0.0120%16 Sept →
dust24–13-0.0220%16 Sept →
anubis19–160.0112%15 Sept →
ancient0–13-0.0815%15 Sept →
nuke13–7-0.0223%11 Sept →
inferno13–11-0.048%11 Sept →
nuke9–13-0.0419%11 Sept →
inferno13–7-0.0319%11 Sept →
overpass8–80.049%10 Sept →
inferno0–9-0.228%10 Sept →
inferno13–6-0.0319%10 Sept →
cache2–11-0.0467%10 Sept →
cache13–5-0.0020%8 Sept →
inferno13–16-0.0712%8 Sept →
cache2–13-0.0617%6 Sept →
cache7–13-0.0326%6 Sept →
cache16–130.0211%6 Sept →
mirage12–16-0.0217%5 Sept →
mirage5–130.0422%5 Sept →
inferno5–130.0117%5 Sept →
cache13–11-0.027%4 Sept →
anubis13–100.0116%4 Sept →
nuke13–90.0212%4 Sept →
cache11–13-0.0218%3 Sept →
inferno13–6-0.0222%3 Sept →
cache13–30.0220%3 Sept →
cache7–130.0214%3 Sept →
cache13–40.0518%2 Sept →
cache13–9-0.0215%1 Sept →
cache4–13-0.0718%1 Sept →
anubis13–8-0.057%1 Sept →
mirage11–13-0.0219%1 Sept →
anubis13–11-0.0126%1 Sept →
inferno13–8-0.098%1 Sept →
mirage16–14-0.0512%1 Sept →
nuke13–10-0.0327%31 Aug →
mirage13–100.0412%31 Aug →
anubis7–130.0223%31 Aug →
mirage16–140.038%30 Aug →
anubis2–13-0.0814%30 Aug →
nuke5–13-0.0920%30 Aug →
nuke16–12-0.0115%26 Aug →
nuke16–120.0313%26 Aug →
cache5–13-0.062%26 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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