alika

alika — CS2 Stats

FI76561199166000755[U:1:1205735027]Steam profile ↗✓ No bans

479Tracked matches57%Win rate2021Tracked since
CSDB Rating6.7 SolidAll-Rounder
CSDB Leaderboard#67556 of 251989 tracked
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 20,987 +2,304 14 Mar – 11 Jun · 26 days played
16,86320,987peak 20,98714 Mar11 Jun
21,091Peak Premier in tracked matches
33Days played since 2025-03-14

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

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

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Performance scores

Aim69
Positioning63
Utility69

0–100 skill scores via Leetify.

Recent form

STEADY49–44–7Last 10049%Win rateLWWWWLWLLW

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · +6.4pp headshot accuracy · −29ms 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

  • 4–1 · 80% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 19%
  • Avg reaction 549ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 19%
  • Avg reaction 533ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 16%
  • Avg reaction 547ms

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.

Aim6.9
Utility6.9
Positioning6.3
Opening Duels5.4
Clutch6.0

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

jL

Plays most like jL 79% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Strengths

CT openings. 65% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 65% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim6.9
Positioning6.3
Utility6.9
Mechanics7.1
Opening Duels5.0
Win Impact7.4

Composite 6.7/10 (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+0.01
first ⅓ avg 0.02 → last ⅓ avg 0.02
Reaction time554ms−49ms
first ⅓ avg 602ms → last ⅓ avg 554ms
Headshot accuracy15.5%+0.8%
first ⅓ avg 14.7% → last ⅓ avg 15.5%

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

0.12Best match rating · 7–0 · overpass, 30 Jul →
36%Best headshot accuracy · 3–13 · train, 16 May →
398msFastest reaction time · 13–11 · ancient, 24 Jul →
13–2Biggest win · ancient, 14 Mar →

Across the last 100 tracked matches.

Highlights

4Longest win streak
10–7In matches decided by ≤2 rounds
14Overtime games

Map breakdown

ancientBest map · 70% over 20dust2Weakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
nukeS2013–765%0.03
ancientS2014–670%0.02
anubisC207–1335%0.01
infernoC176–1135%0.02
dust2D61–517%-0.00
trainD62–433%0.04
overpassA53–260%0.06
mirageC52–340%0.02
jura—11–0100%-0.02

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

207Matches
50%Win rate
1.12Avg K/D
95.5ADR
36%Headshot %

Clutches & streaks

50%1v1 clutch win
33%1v2 clutch win
8Longest win streak

Recent Faceit resultsWWWWW

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.

15.3%Headshot accuracy
33.4%Accuracy (enemy spotted)
34.5%Spray accuracy
82.0%Counter-strafing
8.9°Preaim
556msReaction time
34.8%T opening success
65.0%CT opening success
0.51Enemies flashed / flash
6.9%Flash assists
7.65HE damage / grenade
10.93Flashes / 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 34.757% — below the 40% mark we flag

Spend your practice time on Dust 2

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust29–13-0.048%30 Jul →
nuke13–90.0021%30 Jul →
jura9–0-0.0225%30 Jul →
overpass7–00.1225%30 Jul →
overpass13–30.0617%29 Jul →
overpass9–130.0821%24 Jul →
ancient13–110.0616%24 Jul →
ancient8–13-0.0118%3 Jul →
inferno6–13-0.0618%11 Jun →
inferno13–50.0924%11 Jun →
anubis6–13-0.0318%11 Jun →
ancient13–110.0216%9 Jun →
nuke11–130.0519%9 Jun →
anubis13–110.0316%9 Jun →
anubis13–100.0618%8 Jun →
ancient13–100.0210%8 Jun →
inferno16–14-0.0010%8 Jun →
ancient7–13-0.022%5 Jun →
train7–130.0511%4 Jun →
nuke13–30.049%3 Jun →
anubis10–13-0.0012%3 Jun →
nuke13–100.049%3 Jun →
ancient10–13-0.0220%3 Jun →
anubis13–40.0323%2 Jun →
mirage2–13-0.0025%2 Jun →
anubis15–150.019%31 May →
ancient13–10-0.027%31 May →
inferno13–80.0813%31 May →
nuke11–130.0217%31 May →
inferno15–150.0722%30 May →
ancient1–13-0.039%30 May →
nuke13–70.036%29 May →
ancient13–60.1020%29 May →
anubis13–60.0315%29 May →
nuke8–130.028%29 May →
overpass13–5-0.047%28 May →
mirage12–120.0212%28 May →
mirage13–80.0821%28 May →
nuke8–13-0.0015%28 May →
ancient13–4-0.0112%28 May →
anubis13–16-0.048%28 May →
nuke16–14-0.0312%27 May →
ancient7–130.0017%27 May →
overpass12–120.078%23 May →
inferno13–60.0826%21 May →
train12–60.0518%21 May →
inferno8–13-0.0211%19 May →
ancient13–30.1015%19 May →
nuke13–9-0.0118%19 May →
train3–13-0.0136%16 May →
anubis5–130.0615%15 May →
nuke13–90.0617%15 May →
inferno6–13-0.0219%15 May →
mirage13–110.0911%15 May →
anubis10–130.0316%15 May →
inferno11–130.0211%13 May →
ancient13–100.0310%13 May →
nuke16–14-0.0113%13 May →
inferno13–30.0221%13 May →
anubis13–16-0.0511%13 May →
dust28–130.0222%10 May →
anubis5–13-0.0310%10 May →
ancient13–100.0315%10 May →
dust212–160.0113%9 May →
nuke10–13-0.0313%9 May →
train9–130.0712%9 May →
ancient13–80.0524%9 May →
nuke12–60.0623%9 May →
inferno15–15-0.0212%9 May →
anubis13–100.0317%9 May →
nuke13–40.117%8 May →
train14–16-0.0313%8 May →
ancient13–70.027%8 May →
anubis9–130.0113%8 May →
inferno9–130.0011%6 May →
anubis13–70.0519%6 May →
ancient11–13-0.0414%6 May →
nuke13–30.1219%29 Apr →
dust210–13-0.0021%29 Apr →
inferno10–130.0930%29 Apr →
anubis8–13-0.0612%29 Apr →
ancient13–60.0510%29 Apr →
dust213–110.0320%28 Apr →
nuke6–130.0518%28 Apr →
inferno6–10.0219%28 Apr →
ancient13–10-0.0117%23 Apr →
anubis12–160.0216%17 Apr →
mirage4–13-0.0812%17 Apr →
anubis16–14-0.0110%5 Apr →
nuke15–150.0416%5 Apr →
inferno9–130.0222%5 Apr →
inferno11–13-0.0315%24 Mar →
anubis15–150.059%24 Mar →
inferno3–13-0.0514%14 Mar →
dust211–13-0.0213%14 Mar →
train13–100.119%14 Mar →
anubis3–13-0.0413%14 Mar →
ancient13–20.0520%14 Mar →
nuke13–110.0311%14 Mar →
nuke13–80.076%14 Mar →

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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