Litranjuissi

Litranjuissi — CS2 Stats

FI76561198121357222[U:1:161091494]Steam profile ↗✓ No bans

330Tracked matches54%Win rate2021Tracked since
494Hours in CS
CSDB Rating3.6 LearningPositional Player
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 2,906 -6,530 27 Oct – 13 Nov · 8 days played
2,5789,436peak 9,43627 Oct13 Nov
9,559Peak Premier in tracked matches
51Days played since 2024-10-27

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

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=14,312), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 4 medianLevel 5 medianvs Level 5
Headshot rate35.1%42.7%43.7%8.6% short
Shot accuracy15.8%11.3%12.0%above
Kill/death ratio0.780.991.020.23 short
Match win rate33.6%43.9%44.7%11.1% short

This profile matches the typical Level 5 player on 1 of 4 comparable metrics.

Widest gap: Match win rate. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGLitranjuissiFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim34
Positioning46
Utility14

0–100 skill scores via Leetify.

Recent form

HOT44–54–2Last 10044%Win rateWWWLWWLLWW

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · −0.7pp headshot accuracy · −10ms reaction

Win rate up 20pp 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 -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 717ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 741ms

Last 20

  • 12–6–2 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 746ms

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 (+2.1 against its own average).

Aim3.4
Utility1.4
Positioning4.6
Opening Duels2.1
Clutch1.8

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

jL

Plays most like jL 78% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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. 753ms 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

Aim3.4
Positioning4.6
Utility1.4
Mechanics4.4
Opening Duels1.9
Win Impact6.2

Composite 3.6/10 (Learning), 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-0.02+0.03
first ⅓ avg -0.05 → last ⅓ avg -0.02
Reaction time759ms−15ms
first ⅓ avg 774ms → last ⅓ avg 759ms
Headshot accuracy13.7%+0.2%
first ⅓ avg 13.5% → last ⅓ avg 13.7%

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

0.08Best match rating · 13–1 · nuke, 13 Nov →
38%Best headshot accuracy · 13–3 · mirage, 22 Nov →
422msFastest reaction time · 0–13 · ancient, 12 Jun →
13–0Biggest win · dust2, 15 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W3Current streak
7–6In matches decided by ≤2 rounds
1Overtime games

Map breakdown

nukeBest map · 67% over 15anubisWeakest map · 0% over 10
MapGradePlayedRecordWin rateAvg rating
dust2D164–1225%-0.04
mirageB168–850%-0.03
nukeS1510–567%-0.04
trainC156–940%-0.03
ancientS128–467%-0.04
anubisD100–100%-0.05
infernoD61–517%-0.09
edin—31–233%-0.02
cache—22–0100%-0.07
vertigo—21–150%-0.07
overpass—11–0100%-0.02
basalt—11–0100%0.06
thera—11–0100%0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (0% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

21,157Lifetime kills
0.78K/D
1,392Matches
33.6%Match win rate
35.1%Headshot %
15.8%Shot accuracy · Top 25% of Level 4 players
2,114MVPs
494Hours (in match)
1,018Bombs planted
140Bombs defused

Most-used weapons

Lifetime map wins

1,901dust2
928nuke
644inferno
335train
199lake
192vertigo
81cbble
34assault

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

14Matches
57%Win rate
0.64Avg K/D
58.8ADR
36%Headshot %

Clutches & streaks

29%1v1 clutch win
29%1v2 clutch win
4Longest win streak

Recent Faceit resultsLWLLW

MapMatchesWin rateAvg K/DAvg kills
Anubis771%0.8113.4
Mirage333%0.429.7
Nuke250%0.344.5
Dust21100%0.9019.0
Inferno10%0.5211.0

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.

13.2%Headshot accuracy
34.2%Accuracy (enemy spotted)
37.0%Spray accuracy
70.0%Counter-strafing
11.4°Preaim
753msReaction time
36.4%T opening success
38.7%CT opening success
0.33Enemies flashed / flash
5.2%Flash assists
8.23HE damage / grenade
2.26Flashes / 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 13.236% — below the 15% mark we flag

    Aim Training →
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 753.0067ms — above the 700ms mark we flag

    Aim Training →
  3. 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 0.3307 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Anubis

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

0% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–10-0.076%18 May →
cache9–4-0.088%18 May →
dust213–11-0.0316%14 Mar →
anubis11–13-0.0410%14 Mar →
overpass13–7-0.0224%11 Mar →
nuke13–10.0815%13 Nov →
mirage6–130.0415%13 Nov →
dust23–130.0414%22 Oct →
ancient13–8-0.0816%22 Oct →
mirage13–100.0411%19 Oct →
mirage13–6-0.0217%16 Oct →
nuke13–2-0.0118%14 Oct →
ancient13–20.048%14 Oct →
nuke13–11-0.053%7 Oct →
anubis12–12-0.017%28 Sept →
inferno8–13-0.068%24 Sept →
train10–13-0.0116%18 Sept →
ancient10–13-0.0111%18 Sept →
train12–12-0.0419%15 Sept →
dust213–00.0435%15 Sept →
nuke8–13-0.0715%12 Sept →
ancient13–11-0.067%12 Sept →
mirage1–13-0.0422%10 Sept →
mirage9–130.0113%10 Sept →
dust24–13-0.0116%10 Sept →
nuke6–13-0.125%10 Sept →
nuke13–80.0318%7 Sept →
ancient7–13-0.058%3 Sept →
mirage4–13-0.0414%3 Sept →
nuke13–11-0.0517%31 Aug →
train13–10-0.0316%31 Aug →
train13–1-0.080%25 Aug →
dust28–13-0.0525%25 Aug →
ancient13–9-0.0314%25 Aug →
inferno3–13-0.109%25 Aug →
mirage14–16-0.0219%24 Aug →
inferno2–13-0.0413%24 Aug →
dust211–13-0.0512%8 Aug →
mirage13–5-0.0319%8 Aug →
dust23–13-0.0622%8 Aug →
nuke8–13-0.0315%30 Jul →
dust26–13-0.097%12 Jun →
ancient0–13-0.060%12 Jun →
nuke6–20.0018%10 Jun →
anubis7–13-0.0511%2 Jun →
nuke13–9-0.0515%2 Jun →
train6–13-0.0110%27 May →
train6–13-0.0020%11 May →
edin9–13-0.0414%5 May →
vertigo6–9-0.1117%5 May →
dust210–130.0316%4 May →
train13–80.016%4 May →
mirage13–10-0.053%30 Apr →
nuke13–6-0.1012%30 Apr →
dust213–10-0.019%29 Apr →
mirage9–13-0.067%27 Apr →
train9–130.024%24 Apr →
inferno6–13-0.1113%24 Apr →
mirage13–11-0.0213%23 Apr →
nuke13–2-0.0312%23 Apr →
inferno13–11-0.0916%23 Apr →
anubis8–13-0.079%23 Apr →
dust29–13-0.098%31 Jan →
dust213–6-0.0511%30 Jan →
ancient11–130.0011%29 Jan →
dust211–13-0.0614%26 Jan →
vertigo13–4-0.0210%26 Jan →
anubis8–13-0.100%26 Jan →
nuke10–13-0.095%6 Jan →
mirage7–13-0.0118%4 Jan →
anubis2–13-0.0913%4 Jan →
ancient13–5-0.068%4 Jan →
train9–13-0.0914%6 Dec →
mirage13–7-0.0613%6 Dec →
nuke13–00.0010%6 Dec →
train6–13-0.106%1 Dec →
anubis6–130.0310%1 Dec →
dust25–13-0.0813%22 Nov →
mirage13–30.0238%22 Nov →
mirage13–9-0.0423%22 Nov →
train4–13-0.0612%22 Nov →
edin13–8-0.0221%22 Nov →
train13–10-0.016%17 Nov →
ancient13–8-0.0511%17 Nov →
train13–60.0122%16 Nov →
ancient13–9-0.1013%16 Nov →
anubis2–13-0.090%16 Nov →
train13–9-0.0411%14 Nov →
edin0–40.000%14 Nov →
basalt13–90.0611%14 Nov →
train7–13-0.0412%14 Nov →
nuke5–13-0.0914%12 Nov →
thera13–20.0227%11 Nov →
anubis0–13-0.0922%11 Nov →
mirage3–13-0.1211%11 Nov →
dust211–13-0.0711%11 Nov →
anubis6–13-0.049%1 Nov →
inferno0–13-0.1612%29 Oct →
dust27–13-0.0628%27 Oct →
ancient13–11-0.0523%27 Oct →

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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