ternox

ternox — CS2 Stats

TN76561198924512439[U:1:964246711]Steam profile ↗✓ No bans

36Tracked matches48%Win rate2023Tracked since
CSDB Rating4.5 Developing
Ladder ranks via Leetify

Performance scores

Aim52
Positioning51
Utility42

0–100 skill scores via Leetify.

Recent form

COLD16191Last 3644%Win rateLLLLLWLWLW

Last 10 vs previous 10: -50pp win rate · +0.01 avg rating

Player DNA

Aim5.2
Aggression5.4
Utility4.2
Positioning5.1
Opening Duels2.0

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 83% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower utility contribution; 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 50% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 569ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.2
Positioning5.1
Utility4.2
Mechanics4.2
Opening Duels2.5
Win Impact4.4

Composite 4.5/10 (Developing), 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 rating0.04+0.06
first ⅓ avg -0.02 → last ⅓ avg 0.04
Reaction time551ms−37ms
first ⅓ avg 587ms → last ⅓ avg 551ms
Headshot accuracy19.0%+7.6%
first ⅓ avg 11.3% → last ⅓ avg 19.0%

Rolling 5-match average across the last 36 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.25Best rating — train 13–0
130Biggest win — train
4Longest win streak
L5Current streak
32In matches decided by ≤2 rounds
14Overtime games

Map breakdown

nukeBest map · 80% over 5infernoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
infernoD61517%-0.02
mirageD62433%0.01
ancientA53260%0.06
nukeS54180%0.00
dust23030%-0.05
train330100%0.07
overpass31233%-0.01
anubis31233%-0.01
vertigo1010%-0.03
cache110100%0.07

Across the last 36 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

15.2%Headshot accuracy
36.2%Accuracy (enemy spotted)
36.9%Spray accuracy
68.7%Counter-strafing
12.8°Preaim
569msReaction time
26.3%T opening success
50.0%CT opening success
0.70Enemies flashed / flash
7.1%Flash assists
12.23HE damage / grenade
5.52Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.757° — above the 12° mark we flag

    Aim Training
Spend your practice time on Inferno

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
dust28–13-0.0224%28 Jul
inferno5–13-0.0116%6 Jul
dust25–13-0.0819%6 Jul
mirage10–13-0.0317%6 Jul
ancient11–130.108%29 Jun
train13–00.2518%17 Jun
overpass10–130.0118%17 Jun
anubis16–120.0124%16 Jun
ancient8–130.0213%3 Jun
mirage13–50.1428%3 Jun
ancient13–90.1130%21 May
mirage13–110.0214%21 May
ancient13–80.0219%13 May
mirage12–160.0114%13 Dec
inferno16–140.0411%28 Aug
nuke13–50.0818%28 Aug
train7–1-0.047%28 Aug
nuke16–120.0117%19 Apr
anubis8–13-0.037%11 Feb
ancient10–10.0711%11 Feb
mirage14–16-0.0212%11 Feb
mirage1–13-0.0411%1 Feb
train13–70.0012%1 Feb
inferno8–13-0.0712%21 Jan
inferno4–13-0.0619%5 Oct
overpass1–130.000%29 Sept
vertigo7–16-0.0317%3 Jun
nuke16–11-0.0110%3 Jun
inferno15–150.018%3 May
nuke16–60.0110%3 May
cache5–30.070%12 Apr
overpass16–13-0.0318%12 Apr
dust211–16-0.0518%7 Apr
inferno10–16-0.0321%7 Apr
anubis8–16-0.028%6 Apr
nuke7–16-0.098%6 Apr

Match data via Leetify.

Recent teammates

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