AxL

AxL — CS2 Stats

76561198024509769[U:1:64244041]Steam profile ↗✓ No bans

703Tracked matches30%Win rate2020Tracked since
CSDB Rating5.7 SolidSupport
FaceitLevel 10Top 12.4% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Sep 2026 (7 days ago). Ranks are recorded once per day this page is viewed.

+4Tracked matches · now 703
−10.0ppWin rate · 40.0% → 30.0%
Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 62 days played since 12 May 2025. Come back after the next session and the change shows above.

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Rating over time

23,573Peak Premier in tracked matches
62Days played since 2025-05-12

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

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CSDB.GGAxLFACEITLevel 10STANDINGTop 12.4% of rankedcsdb.gg/stats

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Performance scores

Aim78
Positioning58
Utility65

0–100 skill scores via Leetify.

Recent form

STEADY5248Last 10052%Win rateLLLLWLWWLW

Last 10 vs previous 10: +10pp win rate · −0.03 avg rating · −0.5pp headshot accuracy · +9ms reaction

Win rate +10pp 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

  • 14 · 20% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 12%
  • Avg reaction 526ms

Last 10

  • 46 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 14%
  • Avg reaction 530ms

Last 20

  • 713 · 35% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 526ms

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: SupportUtility contribution stands above the rest of this profile (+1.9 against its own average).

Aim7.8
Utility6.5
Positioning5.8
Opening Duels4.3
Clutch1.8

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 89% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Aim7.8
Positioning5.8
Utility6.5
Mechanics6.0
Opening Duels3.7
Win Impact0.0

Composite 5.7/10 (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 rating0.01−0.01
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time552ms−57ms
first ⅓ avg 609ms → last ⅓ avg 552ms
Headshot accuracy15.3%+1.1%
first ⅓ avg 14.2% → last ⅓ avg 15.3%

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 · 13–8 · train, 2 Aug
40%Best headshot accuracy · 5–13 · cache, 8 Aug
367msFastest reaction time · 11–13 · vertigo, 29 Aug
13–2Biggest win · cache, 27 Jun

Across the last 100 tracked matches.

Highlights

5Longest win streak
L4Current streak
1111In matches decided by ≤2 rounds
15Overtime games

Map breakdown

nukeBest map · 69% over 13ancientWeakest map · 31% over 13
MapGradePlayedRecordWin rateAvg rating
mirageC145936%0.00
cacheC146843%0.01
nukeS139469%0.01
infernoS139469%0.03
ancientD134931%0.01
dust2A116555%0.03
overpassA74357%-0.01
trainS64267%0.03
anubis42250%-0.01
cache_b43175%0.04
vertigo1010%0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

528Matches
55%Win rate
1.22Avg K/D
76.9ADR
31%Headshot %

Clutches & streaks

29%1v1 clutch win
19%1v2 clutch win
8Longest win streak

Recent Faceit resultsLWLWW

MapMatchesWin rateAvg K/DAvg kills
Inferno862%1.0515.1
Mirage475%0.7512.8
Nuke450%0.9119.8
Anubis333%0.9515.3
Train367%0.9913.3
Dust23100%1.8217.3
Ancient20%0.8213.5
Overpass1100%1.5018.0

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.

15.1%Headshot accuracy
37.0%Accuracy (enemy spotted)
43.3%Spray accuracy
77.0%Counter-strafing
9.0°Preaim
540msReaction time
39.8%T opening success
50.2%CT opening success
0.54Enemies flashed / flash
6.2%Flash assists
9.56HE damage / grenade
10.82Flashes / 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 39.8057% — 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.

31% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
mirage7–13-0.0012%18 Sept
dust26–130.0715%15 Sept
dust24–13-0.038%15 Sept
train10–130.0213%15 Sept
nuke13–110.0514%9 Sept
overpass8–13-0.0517%9 Sept
inferno13–10-0.0316%8 Sept
cache16–130.0013%8 Sept
ancient4–13-0.0320%8 Sept
mirage13–100.0112%8 Sept
ancient13–160.0413%7 Sept
anubis13–100.0715%4 Sept
ancient8–13-0.0210%4 Sept
dust29–130.0717%29 Aug
vertigo11–130.0114%29 Aug
cache14–160.0116%29 Aug
inferno13–70.0715%29 Aug
mirage11–110.0916%29 Aug
inferno11–13-0.0010%29 Aug
nuke13–6-0.0318%27 Aug
nuke6–13-0.0414%26 Aug
cache14–16-0.0115%26 Aug
inferno13–80.0517%26 Aug
mirage9–130.0116%21 Aug
cache9–130.0313%16 Aug
overpass4–13-0.038%8 Aug
cache5–13-0.0540%8 Aug
ancient21–250.0311%5 Aug
inferno11–13-0.0026%5 Aug
cache19–160.0216%5 Aug
anubis3–13-0.1017%4 Aug
dust213–110.0112%3 Aug
train13–9-0.0516%3 Aug
overpass13–80.049%3 Aug
train13–80.1215%2 Aug
anubis13–9-0.0319%2 Aug
cache6–130.0121%2 Aug
mirage13–10-0.069%1 Aug
inferno13–40.0819%30 Jul
cache16–130.0118%21 Jul
inferno13–50.0211%6 Jul
cache11–13-0.0112%6 Jul
ancient13–11-0.0013%6 Jul
overpass5–13-0.0119%5 Jul
cache13–60.0614%1 Jul
nuke13–4-0.0012%30 Jun
dust20–9-0.0827%29 Jun
ancient13–40.1216%28 Jun
cache8–130.0625%28 Jun
inferno6–13-0.006%27 Jun
cache13–20.0327%27 Jun
cache16–14-0.0210%18 Jun
ancient5–13-0.0417%31 May
nuke3–13-0.0318%17 May
cache7–13-0.0310%17 May
inferno13–110.0711%17 May
inferno13–70.029%15 May
ancient8–130.029%19 Apr
cache_b16–140.0514%21 Mar
cache_b16–130.0525%15 Mar
inferno16–140.057%1 Mar
overpass19–15-0.0211%26 Feb
nuke11–13-0.0118%25 Feb
inferno13–50.1219%17 Feb
nuke13–50.0926%5 Jan
mirage10–13-0.029%3 Jan
ancient11–130.0014%3 Jan
nuke9–70.129%27 Dec
mirage7–13-0.0110%21 Dec
train5–13-0.0517%20 Dec
mirage2–13-0.0319%12 Dec
dust28–130.029%4 Dec
dust213–6-0.0415%30 Nov
dust213–50.0513%29 Nov
anubis9–130.0020%23 Nov
nuke13–100.0325%23 Nov
cache_b8–13-0.0111%23 Nov
cache_b13–90.0619%22 Nov
mirage11–13-0.0211%8 Nov
ancient6–13-0.0514%8 Nov
mirage13–11-0.0021%7 Nov
nuke13–70.0113%7 Nov
ancient13–100.058%5 Nov
dust213–40.1224%5 Nov
mirage10–130.0520%4 Nov
overpass6–2-0.0517%1 Nov
ancient13–100.0114%1 Nov
train13–80.049%1 Nov
dust216–140.0313%5 Oct
nuke19–17-0.0012%24 Aug
mirage9–13-0.0212%23 Aug
overpass13–80.0221%21 Aug
ancient11–13-0.0116%30 Jul
mirage13–5-0.0119%30 Jul
nuke16–19-0.0310%5 Jul
nuke13–8-0.023%5 Jun
inferno3–13-0.019%31 May
train13–80.076%31 May
mirage13–80.0118%12 May
dust213–40.0714%12 May

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 10500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →