ted — CS2 Stats

US76561198103212573[U:1:142946845]Steam profile ↗✓ No bans

909Tracked matches59%Win rate2022Tracked since

1,211Hours in CS1Hrs last 2 wks

CSDB Rating3.4 Learning

Premier CS Rating6,610Light Blue band · top ~71.1% of ranked players (population est.)

CSDB Leaderboard#10518 of 13957 tracked

FaceitLevel 4Top 81.0% of ranked FACEIT players

WingmanDistinguished Master Guardian

Ladder ranks via Leetify

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Performance scores

Aim48

Positioning38

Utility13

0–100 skill scores via Leetify.

Recent form

STEADY52–42–6Last 10052%Win rateTWLLLWLWWT

Last 10 vs previous 10: +10pp win rate · +0.03 avg rating

Player DNA

Aim4.8

Aggression3.4

Utility1.3

Positioning3.8

Opening Duels0.0

Clutch0.0

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

Plays most like NiKo 70% playstyle similarity

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

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Counter-strafing. Only 66% 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

Aim4.8

Positioning3.8

Utility1.3

Mechanics3.5

Opening Duels0.0

Win Impact8.1

Composite 3.4/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01+0.00

first ⅓ avg -0.01 → last ⅓ avg -0.01

Reaction time560ms−40ms

first ⅓ avg 600ms → last ⅓ avg 560ms

Headshot accuracy17.5%+5.7%

first ⅓ avg 11.8% → last ⅓ avg 17.5%

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

0.09Best rating — office 4–0

13–2Biggest win — inferno

7Longest win streak

1–4In matches decided by ≤2 rounds

Map breakdown

infernoBest map · 100% over 6dust2Weakest map · 27% over 11

Map	Grade	Played	Record	Win rate	Avg rating
office	A	39	23–16	59%	-0.01
dust2	D	11	3–8	27%	-0.03
cache	B	11	5–6	45%	-0.04
train	C	8	3–5	38%	0.00
inferno	S	6	6–0	100%	0.03
mirage	C	5	2–3	40%	-0.03
shelter	—	4	2–2	50%	-0.02
ancient	—	4	1–3	25%	-0.01
anubis	—	3	1–2	33%	-0.03
vertigo	—	3	3–0	100%	-0.01
nuke	—	3	1–2	33%	-0.01
italy	—	1	1–0	100%	0.07
overpass	—	1	0–1	0%	-0.06
warden	—	1	1–0	100%	-0.05

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

28,496Lifetime kills

0.83K/D

2,016Matches

44.4%Match win rate

39.3%Headshot %

8.2%Shot accuracy

5,298MVPs

682Hours (in match)

1,811Bombs planted

842Bombs defused

Most-used weapons

AK-478,495

M4A4 / M4A1-S7,584

P2000 / USP-S2,343

AWP2,089

Glock-181,545

XM10141,027

Negev661

P90653

Galil AR598

UMP-45463

Lifetime map wins

3,771dust2

3,076office

2,023nuke

1,365inferno

500vertigo

390train

138italy

46cbble

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

14Matches

36%Win rate

0.61Avg K/D

65.7ADR

37%Headshot %

Clutches & streaks

20%1v1 clutch win

67%1v2 clutch win

2Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	3	33%	0.65	14.7
Dust2	3	33%	0.58	9.3
Nuke	1	0%	0.89	16.0
Thera	1	100%	0.50	12.0
Anubis	1	0%	0.42	8.0
Train	1	0%	0.55	11.0

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.

17.6%Headshot accuracy

28.8%Accuracy (enemy spotted)

27.8%Spray accuracy

65.7%Counter-strafing

9.3°Preaim

542msReaction time

24.8%T opening success

29.5%CT opening success

0.08Enemies flashed / flash

0.0%Flash assists

11.37HE damage / grenade

0.42Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.0794 — below the 0.5 mark we flag
Grenade Lineups →
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 24.8173% — below the 40% mark we flag

Spend your practice time on Dust 2

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

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
office	12–12	0.03	9%	25 Aug →
office	13–5	-0.01	20%	25 Aug →
office	8–13	-0.08	50%	12 Aug →
office	8–13	0.08	28%	30 Jul →
office	11–13	0.03	23%	29 Jul →
office	13–10	-0.00	18%	29 Jul →
office	5–13	-0.02	15%	27 Jul →
office	13–6	-0.02	6%	27 Jul →
office	13–10	0.00	10%	26 Jul →
office	12–12	0.06	16%	26 Jul →
office	4–13	-0.06	0%	26 Jul →
anubis	10–13	-0.03	16%	25 Jul →
office	4–0	0.09	0%	25 Jul →
shelter	8–13	-0.08	13%	17 Jul →
shelter	13–3	0.07	28%	16 Jul →
office	10–13	-0.06	11%	16 Jul →
office	8–13	-0.04	6%	12 Jul →
train	3–13	-0.07	15%	12 Jul →
train	9–13	-0.05	17%	12 Jul →
office	13–8	-0.01	21%	11 Jul →
vertigo	13–7	0.00	15%	11 Jul →
office	13–8	-0.03	31%	11 Jul →
shelter	13–10	-0.06	22%	9 Jul →
shelter	12–12	-0.02	30%	9 Jul →
office	13–5	-0.01	15%	8 Jul →
office	13–3	-0.06	11%	8 Jul →
italy	13–3	0.07	17%	8 Jul →
office	13–5	-0.04	8%	8 Jul →
inferno	13–7	0.09	22%	4 Jul →
nuke	13–5	0.04	16%	4 Jul →
dust2	13–8	-0.04	33%	4 Jul →
ancient	3–13	-0.05	16%	4 Jul →
cache	13–9	-0.05	18%	2 Jul →
nuke	10–13	-0.05	7%	30 Jun →
office	10–13	-0.03	21%	27 Jun →
office	13–4	-0.02	12%	27 Jun →
overpass	3–13	-0.06	5%	23 Jun →
mirage	13–5	-0.08	0%	23 Jun →
dust2	2–13	-0.05	14%	23 Jun →
cache	13–10	-0.07	16%	21 Jun →
office	6–13	0.04	7%	21 Jun →
office	13–10	-0.04	3%	20 Jun →
office	13–3	-0.02	3%	20 Jun →
office	13–5	0.05	19%	20 Jun →
inferno	13–6	-0.05	11%	20 Jun →
mirage	5–13	-0.04	11%	20 Jun →
office	13–7	0.00	16%	20 Jun →
anubis	8–13	-0.03	10%	20 Jun →
cache	13–8	-0.07	13%	19 Jun →
mirage	9–13	-0.05	15%	19 Jun →
inferno	13–2	0.00	8%	19 Jun →
train	13–3	0.04	11%	19 Jun →
office	13–9	0.03	12%	19 Jun →
office	13–5	-0.00	14%	19 Jun →
office	13–10	0.03	15%	18 Jun →
train	13–11	0.08	10%	17 Jun →
dust2	7–13	-0.04	29%	17 Jun →
train	13–9	0.03	20%	17 Jun →
mirage	9–1	0.08	19%	14 Jun →
dust2	10–13	-0.04	10%	14 Jun →
dust2	10–13	-0.10	0%	14 Jun →
dust2	7–13	-0.06	11%	14 Jun →
nuke	10–13	-0.03	22%	14 Jun →
dust2	6–1	0.04	13%	13 Jun →
office	5–13	0.00	10%	13 Jun →
warden	13–3	-0.05	13%	13 Jun →
office	7–13	-0.04	16%	9 Jun →
office	13–8	0.01	10%	9 Jun →
dust2	4–13	-0.04	25%	8 Jun →
office	7–13	-0.03	0%	8 Jun →
office	13–5	-0.02	20%	4 Jun →
cache	4–13	-0.03	19%	17 May →
inferno	13–6	0.05	21%	17 May →
cache	13–7	0.01	7%	17 May →
anubis	13–5	-0.02	7%	16 May →
cache	12–12	0.01	13%	16 May →
cache	10–13	-0.02	12%	5 May →
inferno	11–6	0.02	3%	5 May →
ancient	7–13	0.04	17%	4 May →
cache	7–13	-0.09	0%	4 May →
office	10–13	-0.01	9%	30 Apr →
office	13–5	0.05	9%	30 Apr →
office	13–9	-0.04	5%	30 Apr →
cache	13–7	-0.04	17%	30 Apr →
cache	11–13	-0.04	5%	29 Apr →
cache	6–13	-0.03	10%	29 Apr →
mirage	3–13	-0.06	13%	20 Apr →
vertigo	13–7	-0.06	8%	20 Apr →
inferno	13–5	0.07	14%	20 Apr →
office	13–10	0.01	15%	17 Apr →
ancient	5–13	-0.04	12%	17 Apr →
train	12–12	0.04	15%	16 Apr →
ancient	13–4	0.02	14%	16 Apr →
train	12–12	-0.06	13%	15 Apr →
vertigo	13–3	0.01	18%	15 Apr →
dust2	13–6	-0.02	12%	15 Apr →
dust2	2–4	-0.01	0%	7 Apr →
dust2	11–13	0.08	9%	1 Apr →
office	10–13	-0.08	12%	26 Feb →
train	6–13	-0.01	24%	25 Feb →