termlol — CS2 Stats

76561197969320749[U:1:9055021]✓ No bans

448Tracked matches55%Win rate2020Tracked since
CSDB Rating6.2 SolidPassive Rifler
Premier CS Rating18,306Purple band · top ~15.2% of ranked players (population est.)
CSDB Leaderboard#8427 of 15757 tracked
FaceitLevel 10Top 12.4% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGtermlolFACEITLevel 10STANDINGTop 12.4% of rankedPREMIER18,306 · Purple bandcsdb.gg/stats

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Performance scores

Aim76
Positioning43
Utility59

0–100 skill scores via Leetify.

Recent form

STEADY53452Last 10053%Win rateLWTLWWWWLW

Last 10 vs previous 10: -10pp win rate · +0.00 avg rating

Player DNA

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

Aim7.6
Aggression3.5
Utility5.9
Positioning4.3
Opening Duels0.4

Excellent counter-strafingStrong CT-side openerEffective flashes

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

NiKo

Plays most like NiKo 86% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower positioning profile; 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

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

T-side openings. Opening success drops from 47% on CT to 16% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 663ms 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

Aim7.6
Positioning4.3
Utility5.9
Mechanics8.5
Opening Duels2.2
Win Impact6.7

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+0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time661ms−1ms
first ⅓ avg 662ms → last ⅓ avg 661ms
Headshot accuracy24.2%−0.1%
first ⅓ avg 24.4% → last ⅓ avg 24.2%

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

0.12Best rating — cache 13–9
131Biggest win — dust2
4Longest win streak
105In matches decided by ≤2 rounds
10Overtime games

Map breakdown

infernoBest map · 88% over 8ancientWeakest map · 38% over 13
MapGradePlayedRecordWin rateAvg rating
mirageB22101245%0.01
dust2B2091145%-0.00
anubisA159660%0.01
ancientC135838%0.02
nukeA117464%0.01
infernoS87188%0.01
cacheS64267%0.04
trainC52340%0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

226Matches
61%Win rate
1.46Avg K/D
ADR
39%Headshot %

Clutches & streaks

1v1 clutch win
1v2 clutch win
12Longest win streak

Recent Faceit resultsLWLLL

MapMatchesWin rateAvg K/DAvg kills
Anubis683%1.3515.8
Ancient333%1.0416.0
Overpass10%0.539.0
Vertigo1100%2.6026.0
Inferno10%1.1714.0
Nuke10%0.6911.0
Dust210%0.6312.0

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.

23.9%Headshot accuracy
35.4%Accuracy (enemy spotted)
36.7%Spray accuracy
88.4%Counter-strafing
10.1°Preaim
663msReaction time
15.9%T opening success
47.5%CT opening success
0.73Enemies flashed / flash
3.2%Flash assists
11.80HE damage / grenade
9.55Flashes / 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 15.9385% — 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.

38% 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
ancient6–130.0125%26 Aug
cache13–40.0531%18 Aug
anubis15–15-0.0121%18 Aug
nuke5–13-0.0522%12 Aug
cache13–9-0.0120%12 Aug
dust213–80.0121%9 Aug
ancient16–140.0519%8 Aug
mirage13–4-0.0122%8 Aug
dust211–130.0232%2 Aug
anubis13–110.0523%2 Aug
ancient8–130.0121%1 Aug
mirage13–90.0515%1 Aug
dust29–130.0333%1 Aug
cache13–90.0237%29 Jul
anubis13–9-0.0323%29 Jul
nuke13–11-0.0518%26 Jul
cache13–90.1231%26 Jul
mirage0–12-0.0517%26 Jul
anubis13–11-0.0317%24 Jul
inferno13–50.0318%24 Jul
dust213–80.0015%24 Jul
anubis5–130.0427%24 Jul
mirage13–160.0242%21 Jul
mirage6–13-0.0214%20 Jul
anubis13–40.0720%20 Jul
nuke13–110.0120%20 Jul
cache6–130.0129%19 Jul
cache6–130.0118%19 Jul
mirage7–13-0.0526%11 Jul
dust211–130.0333%19 May
train7–130.0226%18 May
anubis10–13-0.0425%5 May
nuke6–13-0.0438%4 May
train13–60.0529%4 May
anubis13–11-0.0124%3 May
dust23–13-0.0719%3 May
dust216–140.0129%28 Apr
mirage13–6-0.0210%28 Apr
mirage8–130.0221%27 Apr
ancient6–130.0227%26 Apr
mirage16–130.0114%26 Apr
train13–4-0.057%26 Apr
anubis15–15-0.0016%21 Apr
anubis11–130.0119%20 Apr
ancient3–13-0.0227%20 Apr
dust213–60.0326%20 Apr
anubis13–11-0.0325%6 Apr
mirage13–30.0226%6 Apr
train9–13-0.0121%6 Apr
train6–13-0.0116%6 Apr
ancient8–13-0.0220%30 Mar
inferno13–30.0724%30 Mar
inferno13–40.0018%30 Mar
ancient13–20.0622%30 Mar
ancient13–16-0.057%30 Mar
mirage6–130.0230%30 Mar
dust26–13-0.0417%27 Mar
inferno13–100.0533%27 Mar
mirage13–110.0413%27 Mar
anubis13–80.0213%26 Mar
mirage5–13-0.0127%26 Mar
anubis13–90.0532%24 Mar
ancient8–13-0.0324%24 Mar
inferno7–13-0.0329%23 Mar
dust213–50.1037%23 Mar
mirage9–130.0335%18 Mar
nuke13–100.0719%18 Mar
mirage13–110.0225%16 Mar
dust213–6-0.0633%16 Mar
mirage8–13-0.0136%16 Mar
nuke8–13-0.035%4 Mar
nuke13–50.0521%4 Mar
dust210–130.0021%3 Mar
nuke5–13-0.0113%3 Mar
inferno13–6-0.0320%3 Mar
anubis13–8-0.0048%3 Mar
ancient13–30.1220%3 Mar
mirage8–130.0328%3 Mar
dust212–16-0.0912%27 Feb
mirage11–130.0030%16 Feb
inferno13–10-0.0322%16 Feb
inferno13–50.0338%15 Feb
ancient13–80.0526%15 Feb
nuke13–100.0227%15 Feb
anubis11–13-0.0214%15 Feb
mirage13–6-0.0118%15 Feb
dust28–13-0.0329%8 Feb
mirage16–12-0.0118%2 Feb
ancient13–30.0121%2 Feb
dust25–13-0.0022%2 Feb
mirage13–30.0423%7 Aug
dust26–13-0.0328%21 Jul
ancient5–13-0.0029%6 Jul
dust213–10.0231%26 Jun
dust26–13-0.0218%6 Jun
dust213–8-0.0129%6 Jun
nuke13–60.0842%6 Jun
mirage13–160.0417%1 Jun
dust213–60.0528%1 Jun
nuke13–40.0711%1 Jun

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 10100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →