Lateksi

Lateksi — CS2 Stats

FI76561199040502317[U:1:1080236589]Steam profile ↗✓ No bans

1,430Tracked matches60%Win rate2020Tracked since
CSDB Rating6.6 SolidSupport
CSDB Leaderboard#26216 of 259749 tracked
FaceitLevel 10 · 1,893 ELOTop 12.4% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 24,686 -1,341 21 Oct – 10 Dec · 7 days played
24,63226,027peak 26,02721 Oct10 Dec
26,027Peak Premier in tracked matches
1,893Highest Faceit ELO seen on CSDB
57Days played since 2025-10-03

Faceit ELO

  • At peak — 1,893
  • Next: Level 10 at 2,001 — 108 to go
  • Reached: Level 9 · Level 8 · Level 7 · Level 6

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

Share this profile

CSDB.GGLateksiFACEITLevel 10 · 1,893 ELOSTANDINGTop 12.4% of rankedPEAK ELO1,893csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim79
Positioning65
Utility67

0–100 skill scores via Leetify.

Recent form

STEADY47–52–1Last 10047%Win rateWLLLLLWWLW

Last 10 vs previous 10: −20pp win rate · +0.01 avg rating · −2.1pp headshot accuracy · −53ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 16%
  • Avg reaction 477ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 20%
  • Avg reaction 466ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 21%
  • Avg reaction 492ms

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 (+1.4 against its own average).

Aim7.9
Utility6.7
Positioning6.5
Opening Duels3.8
Clutch4.2

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

ZywOo

Plays most like ZywOo 87% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim7.9
Positioning6.5
Utility6.7
Mechanics6.7
Opening Duels4.5
Win Impact8.3

Composite 6.6/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.01
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time512ms−73ms
first ⅓ avg 585ms → last ⅓ avg 512ms
Headshot accuracy19.1%+3.0%
first ⅓ avg 16.2% → last ⅓ avg 19.1%

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

0.14Best match rating · 13–0 · inferno, 9 Oct →
43%Best headshot accuracy · 1–13 · inferno, 18 Apr →
383msFastest reaction time · 13–9 · inferno, 21 Feb →
13–0Biggest win · inferno, 9 Oct →

Across the last 100 tracked matches.

Highlights

6Longest win streak
9–8In matches decided by ≤2 rounds
11Overtime games

Map breakdown

trainBest map · 67% over 6anubisWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
infernoA2214–864%0.01
ancientB179–853%0.01
nukeD175–1229%-0.01
mirageB168–850%0.01
anubisD92–722%-0.03
dust2D62–433%0.01
trainS64–267%0.02
cache—31–233%0.03
overpass—32–167%-0.00
vertigo—10–10%0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,586Matches
52%Win rate
1.14Avg K/D
87.0ADR
39%Headshot %

Clutches & streaks

41%1v1 clutch win
23%1v2 clutch win
10Longest win streak

Recent Faceit resultsLLWLW

MapMatchesWin rateAvg K/DAvg kills
Inferno17262%1.2117.2
Mirage14145%1.0214.6
Ancient9143%1.1116.4
Nuke8859%1.0816.9
Anubis8554%1.1416.6
Train3253%1.2118.4
Vertigo1656%1.3817.3
Cache911%0.9215.8

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.

18.4%Headshot accuracy
35.0%Accuracy (enemy spotted)
38.8%Spray accuracy
80.2%Counter-strafing
9.3°Preaim
508msReaction time
45.2%T opening success
50.4%CT opening success
0.67Enemies flashed / flash
8.3%Flash assists
11.52HE damage / grenade
7.11Flashes / match

Recommended for you

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.

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–100.079%25 Oct →
cache10–13-0.0121%25 Oct →
anubis9–13-0.0120%23 Oct →
ancient10–130.0521%12 Oct →
anubis10–13-0.0610%10 Oct →
inferno13–160.0420%9 Oct →
mirage13–60.0916%9 Oct →
inferno13–00.1431%9 Oct →
nuke8–13-0.0523%19 Sept →
ancient13–30.0826%19 Sept →
anubis13–80.0216%19 Sept →
inferno13–110.0521%19 Sept →
inferno5–130.0212%17 Sept →
cache13–40.0925%10 Sept →
ancient13–60.0216%10 Sept →
nuke2–13-0.0518%30 Jul →
nuke11–13-0.0523%30 Jul →
mirage13–3-0.0436%30 Jul →
mirage13–10.1130%30 Jul →
nuke7–130.0322%30 Jul →
inferno13–9-0.0116%9 Jun →
anubis13–8-0.067%3 Jun →
ancient7–13-0.0318%3 Jun →
mirage13–40.0121%3 Jun →
nuke13–10-0.0413%2 Jun →
ancient13–50.0724%24 May →
inferno16–14-0.0513%20 May →
mirage13–90.009%20 May →
nuke13–11-0.0319%8 May →
cache7–130.0117%7 May →
nuke13–30.0315%6 May →
ancient13–11-0.0723%5 May →
nuke11–13-0.0223%4 May →
nuke1–13-0.0322%24 Apr →
nuke13–100.019%23 Apr →
inferno1–13-0.0743%18 Apr →
mirage6–13-0.0221%18 Apr →
inferno1–13-0.0618%18 Apr →
anubis6–13-0.0721%18 Apr →
inferno12–60.0216%18 Apr →
mirage4–130.0237%18 Apr →
ancient8–13-0.0623%30 Mar →
dust22–130.0321%30 Mar →
mirage10–130.0113%30 Mar →
anubis10–13-0.0124%27 Mar →
inferno13–60.0227%26 Mar →
inferno13–80.0122%26 Mar →
mirage13–70.0426%24 Mar →
inferno13–40.0317%19 Mar →
inferno16–13-0.0322%17 Mar →
overpass16–14-0.0221%5 Mar →
ancient20–220.0012%5 Mar →
ancient10–130.0116%3 Mar →
ancient13–100.0813%27 Feb →
ancient11–130.0313%24 Feb →
mirage9–13-0.0519%24 Feb →
inferno13–90.0217%21 Feb →
nuke14–160.0416%13 Feb →
inferno13–5-0.0021%13 Feb →
mirage3–13-0.0713%9 Feb →
anubis4–13-0.103%9 Feb →
ancient13–70.028%3 Feb →
inferno16–140.0322%22 Jan →
mirage13–50.0114%20 Jan →
nuke13–11-0.0011%18 Jan →
nuke6–13-0.0415%17 Jan →
inferno5–13-0.0313%16 Jan →
anubis14–16-0.0312%16 Jan →
mirage8–130.0016%18 Dec →
ancient15–150.0112%10 Dec →
train13–100.1220%9 Dec →
mirage6–13-0.0225%4 Dec →
ancient13–60.0119%4 Dec →
mirage3–13-0.0518%2 Dec →
vertigo8–130.0426%23 Nov →
overpass7–13-0.0610%23 Nov →
anubis4–130.0022%22 Nov →
dust25–13-0.0715%22 Nov →
nuke8–130.0030%22 Nov →
dust213–70.0323%22 Nov →
ancient13–10-0.0217%22 Nov →
dust211–130.0218%22 Nov →
inferno2–13-0.086%21 Nov →
inferno10–130.0111%21 Nov →
nuke5–13-0.0011%18 Nov →
train13–90.0712%18 Nov →
ancient5–13-0.0317%18 Nov →
dust211–130.0615%4 Nov →
train5–13-0.0216%4 Nov →
train16–120.0116%2 Nov →
inferno12–16-0.059%30 Oct →
train13–6-0.0112%22 Oct →
ancient13–30.0717%22 Oct →
overpass13–110.0814%21 Oct →
inferno13–110.0824%21 Oct →
nuke9–13-0.0018%21 Oct →
dust213–100.0116%21 Oct →
mirage13–50.1213%21 Oct →
nuke8–13-0.017%9 Oct →
train6–13-0.0616%3 Oct →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 101,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.