Jaxz

Jaxz — CS2 Stats

76561197961207510[U:1:941782]Steam profile ↗

174Tracked matches54%Win rate2022Tracked since
CSDB Rating6.2 SolidHybrid Rifler
Ladder ranks via Leetify

Performance scores

Aim65
Positioning60
Utility63

0–100 skill scores via Leetify.

Recent form

STEADY47485Last 10047%Win rateWWLLTWWLWL

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Primary style: Hybrid RiflerAim-led profile without a single dominant tendency.

Aim6.5
Aggression9.0
Utility6.3
Positioning6.0
Opening Duels3.5
Clutch0.0

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.

Your pro match

jL

Plays most like jL 91% playstyle similarity

Most alike: opening-fight frequency, 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 →

Strengths & areas to improve

Areas to improve

T-side openings. Opening success drops from 57% on CT to 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 649ms 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

Aim6.5
Positioning6.0
Utility6.3
Mechanics7.2
Opening Duels3.5
Win Impact6.3

Composite 6.2/10 (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 rating0.01−0.03
first ⅓ avg 0.04 → last ⅓ avg 0.01
Reaction time647ms+45ms
first ⅓ avg 601ms → last ⅓ avg 647ms
Headshot accuracy23.8%+5.9%
first ⅓ avg 17.9% → last ⅓ avg 23.8%

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.

Highlights

0.35Best rating — train 3–1
130Biggest win — dust2
6Longest win streak
W2Current streak
76In matches decided by ≤2 rounds
10Overtime games

Map breakdown

overpassBest map · 80% over 5trainWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
dust2C25111444%0.01
mirageC2291341%0.01
ancientB21101148%0.03
infernoS107370%0.05
trainC83538%0.08
overpassS54180%-0.01
cache31233%0.03
nuke31233%-0.03
anubis31233%0.03

Across the last 100 tracked matches.

Faceit stats

Combat

15Matches
60%Win rate
1.38Avg K/D
71.1ADR
38%Headshot %

Clutches & streaks

0%1v1 clutch win
33%1v2 clutch win
6Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Anubis10%1.0716.0
Ancient10%1.1515.0

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.

23.1%Headshot accuracy
31.7%Accuracy (enemy spotted)
30.6%Spray accuracy
82.5%Counter-strafing
9.3°Preaim
649msReaction time
30.9%T opening success
57.0%CT opening success
0.67Enemies flashed / flash
6.0%Flash assists
10.70HE damage / grenade
12.36Flashes / 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 30.8678% — below the 40% mark we flag

Spend your practice time on Train

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

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy

Recent matches

MapScoreRatingHS%Date
ancient13–60.0116%17 Aug
mirage13–90.0038%12 Aug
dust27–130.0633%11 Aug
mirage5–13-0.0524%11 Aug
ancient15–150.0111%28 Jul
dust213–10-0.0558%28 Jul
inferno13–40.0412%13 Jul
dust22–13-0.0717%13 Jul
ancient13–60.1026%12 Jul
mirage10–130.0214%10 Jul
cache13–70.0723%10 Jul
cache10–13-0.0120%10 Jul
ancient13–9-0.0216%10 Jul
dust24–13-0.0425%23 Jun
nuke10–13-0.0227%23 Jun
dust28–130.0524%6 Jun
mirage13–90.0120%6 Jun
anubis14–160.0123%6 Jun
ancient13–50.1426%2 Jun
ancient13–11-0.0228%31 May
mirage5–13-0.0310%27 May
inferno13–40.0819%27 May
dust215–15-0.0022%8 May
ancient8–13-0.0414%4 May
dust26–13-0.0532%30 Apr
nuke13–5-0.0420%30 Apr
ancient15–15-0.0017%30 Apr
cache12–120.0432%30 Apr
inferno13–7-0.0022%25 Apr
dust213–110.0423%25 Apr
mirage13–90.0628%25 Apr
ancient13–10.1231%25 Apr
anubis13–70.0435%24 Apr
ancient13–80.0214%24 Apr
dust29–13-0.0130%15 Apr
anubis7–130.0426%12 Apr
dust213–110.0120%17 Mar
inferno13–20.1114%17 Mar
mirage7–13-0.0229%12 Mar
dust213–00.0117%12 Mar
ancient13–80.0524%10 Mar
ancient6–130.0419%10 Mar
inferno13–50.1119%3 Mar
ancient3–13-0.0712%3 Mar
mirage15–150.0630%3 Mar
dust210–13-0.0323%26 Feb
mirage13–70.0932%26 Feb
overpass13–9-0.0517%19 Jan
train3–13-0.0425%19 Jan
ancient7–13-0.0314%27 Dec
dust21–130.0238%27 Dec
dust213–9-0.0212%20 Dec
ancient10–130.0212%20 Dec
mirage11–130.0028%20 Dec
mirage16–14-0.0426%17 Dec
inferno5–13-0.0328%16 Dec
dust212–16-0.0027%16 Dec
mirage13–100.0238%14 Dec
dust23–130.0623%14 Dec
overpass13–40.0222%8 Dec
mirage8–13-0.0215%8 Dec
inferno16–140.0315%6 Dec
mirage10–130.0117%6 Dec
train8–130.0414%1 Dec
ancient6–130.0612%1 Dec
dust211–130.0014%1 Dec
dust213–70.0527%1 Dec
train13–30.1338%28 Nov
inferno9–130.0514%28 Nov
mirage13–90.0421%28 Nov
mirage7–13-0.0517%25 Nov
inferno7–130.0811%25 Nov
ancient7–130.0112%17 Nov
overpass4–13-0.0611%17 Nov
dust23–130.0538%11 Nov
ancient13–80.0612%11 Nov
mirage13–100.0522%11 Nov
train13–80.1119%10 Nov
overpass13–100.0213%10 Nov
mirage9–13-0.0118%10 Nov
train3–10.3516%8 Nov
overpass13–60.0211%3 Nov
dust213–70.1024%3 Nov
dust216–130.0419%29 Oct
mirage11–130.0313%29 Oct
mirage13–60.0817%20 Oct
inferno13–90.0323%20 Oct
dust213–60.0218%12 Oct
dust25–13-0.0215%12 Oct
train12–160.0211%12 Oct
dust213–7-0.0233%2 Oct
mirage6–130.036%2 Oct
ancient8–130.026%26 Sept
ancient9–130.0511%26 Sept
train10–130.0123%26 Sept
dust213–80.0932%15 Sept
nuke1–13-0.0219%15 Sept
train13–11-0.0215%8 Sept
mirage11–13-0.0423%8 Sept
ancient13–110.0112%4 Sept

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 →