CjLP

CjLP — CS2 Stats

76561198012154693[U:1:51888965]Steam profile ↗✓ No bans

819Tracked matches65%Win rate2020Tracked since
CSDB Rating5.9 SolidSupport
FaceitLevel 9 · 1,983 ELOTop 20.7% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

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CSDB.GGCjLPFACEITLevel 9 · 1,983 ELOSTANDINGTop 20.7% of rankedcsdb.gg/stats

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Performance scores

Aim70
Positioning37
Utility82

0–100 skill scores via Leetify.

Recent form

STEADY59356Last 10059%Win rateWLWWWWTLWL

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating

Player DNA

Primary style: SupportUtility contribution leads the profile while opening activity stays low.

Aim7.0
Aggression2.9
Utility8.2
Positioning3.7
Opening Duels0.0
Clutch2.4

Effective flashesHigh utility contribution

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

Twistzz

Plays most like Twistzz 78% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-fight frequency.

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

Flashes. 0.79 enemies blinded per flash — utility that consistently lands.

Utility. Utility score of 82 — grenade impact well above the norm.

Areas to improve

Positioning. Positioning trails aim by 33 points — deaths here waste a strong aim profile.

Reaction time. 634ms 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

Aim7.0
Positioning3.7
Utility8.2
Mechanics7.3
Opening Duels0.0
Win Impact10.0

Composite 5.9/10 (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 rating-0.01−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time634ms+2ms
first ⅓ avg 632ms → last ⅓ avg 634ms
Headshot accuracy25.2%−0.7%
first ⅓ avg 25.8% → last ⅓ avg 25.2%

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

0.16Best rating — dust2 13–1
131Biggest win — dust2
8Longest win streak
36In matches decided by ≤2 rounds
8Overtime games

Map breakdown

trainBest map · 67% over 6infernoWeakest map · 52% over 25
MapGradePlayedRecordWin rateAvg rating
infernoB25131252%0.01
mirageA2012860%-0.01
ancientA138562%-0.00
dust2B137654%0.00
anubisA85363%-0.00
trainS64267%0.00
nuke43175%0.01
office43175%0.00
grail3030%0.03
overpass220100%0.02
jura110100%-0.03
thera110100%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (52% over 25). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

466Matches
53%Win rate
1.20Avg K/D
78.3ADR
55%Headshot %

Clutches & streaks

32%1v1 clutch win
26%1v2 clutch win
9Longest win streak

Recent Faceit resultsWLLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage7860%1.2516.7
Ancient5250%1.1115.6
Inferno4144%0.9915.0
Vertigo2650%1.1217.0
Anubis1844%1.0415.9
Nuke1464%1.1817.9
Overpass1164%1.3918.7
Dust21040%1.1518.2

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.

25.7%Headshot accuracy
29.9%Accuracy (enemy spotted)
37.6%Spray accuracy
82.7%Counter-strafing
9.9°Preaim
634msReaction time
26.3%T opening success
29.7%CT opening success
0.79Enemies flashed / flash
8.2%Flash assists
11.03HE damage / grenade
19.86Flashes / 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 26.2568% — below the 40% mark we flag

Recent matches

MapScoreRatingHS%Date
overpass16–140.0128%19 Sept
inferno9–13-0.0219%19 Sept
nuke13–80.0230%17 Sept
ancient13–50.0438%17 Sept
overpass13–80.0332%17 Sept
train13–9-0.0119%13 Sept
grail12–120.0520%8 Jul
grail3–130.0326%8 Jul
mirage13–8-0.0233%28 Jun
office4–13-0.0214%28 Jun
office8–2-0.040%28 Jun
dust29–13-0.0133%28 Jun
inferno13–6-0.0416%20 Jun
dust213–7-0.0226%20 Jun
inferno12–120.0221%11 Jun
inferno12–12-0.0143%11 Jun
inferno13–7-0.0016%11 Jun
inferno13–100.0716%11 Jun
mirage12–12-0.0226%6 Jun
inferno11–13-0.0419%6 Jun
mirage13–80.0133%4 Jun
mirage13–80.0030%4 Jun
mirage2–12-0.0343%4 Jun
jura13–8-0.0325%4 Jun
mirage7–13-0.0721%4 Jun
nuke16–120.0736%3 Jun
inferno13–10-0.0730%3 Jun
nuke9–13-0.0327%3 Jun
dust26–13-0.0315%3 Jun
ancient13–10-0.0423%1 Jun
dust28–13-0.0027%31 May
dust213–60.0024%31 May
inferno7–130.0121%31 May
mirage13–50.1114%26 May
ancient8–13-0.0228%26 May
dust210–130.0033%26 May
train12–120.0537%21 May
train7–2-0.0140%21 May
train6–1-0.0350%21 May
inferno8–13-0.0215%16 May
dust213–10-0.0623%16 May
dust213–30.0130%16 May
inferno17–190.0422%13 May
ancient19–16-0.0123%13 May
inferno13–9-0.0123%13 May
ancient10–130.0217%12 May
ancient11–13-0.0446%12 May
dust24–13-0.0329%12 May
anubis13–90.0128%12 May
anubis4–13-0.0316%12 May
mirage16–190.0121%12 May
mirage4–13-0.0727%12 May
inferno13–110.0534%11 May
inferno7–13-0.0141%11 May
mirage13–40.0519%11 May
mirage13–110.0326%10 May
inferno10–130.0443%10 May
inferno13–70.0331%9 May
grail12–120.0222%9 May
ancient13–9-0.0120%9 May
nuke13–8-0.0223%7 May
anubis13–30.0326%7 May
mirage10–13-0.0512%7 May
ancient13–80.0227%7 May
dust213–2-0.0029%6 May
inferno13–60.0627%6 May
dust28–130.0230%6 May
anubis12–16-0.0125%6 May
mirage13–100.0127%6 May
ancient9–130.0421%6 May
inferno9–13-0.0131%6 May
ancient14–16-0.0221%6 May
ancient13–7-0.0332%5 May
ancient13–9-0.0524%1 May
ancient13–40.0432%1 May
inferno13–50.1425%1 May
anubis13–9-0.0227%30 Apr
inferno13–60.0124%30 Apr
mirage13–8-0.0224%30 Apr
anubis6–13-0.0016%30 Apr
mirage13–60.0145%30 Apr
inferno11–13-0.0537%29 Apr
train2–13-0.0236%29 Apr
mirage13–4-0.0432%28 Apr
inferno13–7-0.028%28 Apr
inferno13–4-0.0020%28 Apr
train13–60.0433%28 Apr
mirage11–13-0.0817%28 Apr
dust213–10.1640%27 Apr
mirage7–13-0.0623%2 Sept
thera13–5-0.0120%17 Aug
inferno7–13-0.0426%17 Aug
dust213–4-0.0023%13 Aug
anubis13–70.0228%13 Aug
anubis13–10-0.0118%13 Aug
office13–80.0226%12 Aug
office13–40.0513%12 Aug
mirage13–30.0726%12 Aug
inferno13–100.0329%11 Aug
mirage16–130.0425%11 Aug

Match data via Leetify.

Recent teammates

Milestones

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