Pathos — CS2 Stats

KR76561198329715772[U:1:369450044]Steam profile ↗✓ No bans

1,236Tracked matches45%Win rate2020Tracked since

1,777Hours in CS7Hrs last 2 wks

CSDB Rating4.8 DevelopingPassive Rifler

Premier CS Rating21,074Top 50% of 44,590 CSDB-tracked playersPink band · top ~7.3% of ranked players (population est.)

CSDB Leaderboard#19467 of 60937 tracked

FaceitLevel 4Top 81.0% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

Rating over time

Premier CS Rating: 21,074 +0 30 Aug – 31 Aug · 2 observations

21,074Peak Premier on CSDB

2Days observed since 2026-08-30

Premier CS Rating

At peak — 21,074
Next: Red band at 25,000 — 3,926 to go
Reached: Pink band · Purple band · Blue band · Light Blue band
Pink band first seen 2026-08-30
Purple band first seen 2026-08-30

CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=2,669), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 4 median	Level 5 median	vs Level 5
Headshot rate	43.1%	42.7%	43.7%	meets
Shot accuracy	13.2%	10.8%	11.8%	above
Kill/death ratio	1.28	1.00	1.02	above
Match win rate	51.5%	44.1%	45.0%	above

Across every metric we can compare, this profile already matches the typical Level 5 player. Rank still comes from winning matches — this is a performance comparison, not a prediction.

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Performance scores

Aim74

Positioning42

Utility24

0–100 skill scores via Leetify.

Recent form

STEADY50–43–7Last 10050%Win rateLLLWLWWLWW

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

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim7.4

Aggression3.1

Utility2.4

Positioning4.2

Opening Duels0.4

Clutch2.2

Limited utility dependence

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 b1t 75% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower opening-fight frequency; 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

Positioning. Positioning trails aim by 32 points — deaths here waste a strong aim profile.

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

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

Aim7.4

Positioning4.2

Utility2.4

Mechanics6.2

Opening Duels0.5

Win Impact3.3

Composite 4.8/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.02 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 time558ms−51ms

first ⅓ avg 609ms → last ⅓ avg 558ms

Headshot accuracy14.2%−5.4%

first ⅓ avg 19.6% → last ⅓ avg 14.2%

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

0.15Best rating — alpine 13–6

13–0Biggest win — office

5Longest win streak

L3Current streak

7–7In matches decided by ≤2 rounds

5Overtime games

Map breakdown

mirageBest map · 64% over 11officeWeakest map · 40% over 10

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	21	10–11	48%	-0.00
nuke	B	17	9–8	53%	0.01
ancient	A	13	8–5	62%	-0.01
mirage	A	11	7–4	64%	-0.01
office	C	10	4–6	40%	-0.01
cache	B	6	3–3	50%	-0.00
anubis	B	6	3–3	50%	-0.00
vertigo	A	5	3–2	60%	0.01
train	—	3	2–1	67%	0.05
dust2	—	3	0–3	0%	0.01
overpass	—	2	0–2	0%	0.04
boulder	—	1	0–1	0%	-0.03
italy	—	1	0–1	0%	0.02
alpine	—	1	1–0	100%	0.15

Across the last 100 tracked matches.

Lifetime stats

53,185Lifetime kills

1.28K/D · Top 10% of Level 4 players

3,179Matches

51.5%Match win rate · Top 10% of Level 4 players

43.1%Headshot % · Top 50% of Level 4 players

13.2%Shot accuracy · Top 50% of Level 4 players

10,612MVPs

884Hours (in match)

3,000Bombs planted

743Bombs defused

Most-used weapons

AK-4714,648

M4A4 / M4A1-S7,537

AWP6,497

P2000 / USP-S3,840

Glock-182,954

Desert Eagle2,658

MP71,775

FAMAS1,418

MAC-101,408

MP91,375

Lifetime map wins

4,194inferno

2,461dust2

2,341vertigo

2,276nuke

2,113lake

1,102office

574train

249cbble

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

Faceit stats

Combat

53Matches

42%Win rate

0.84Avg K/D

69.0ADR

41%Headshot %

Clutches & streaks

31%1v1 clutch win

19%1v2 clutch win

4Longest win streak

Recent Faceit resultsLWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	14	43%	0.85	12.6
Inferno	12	50%	0.78	13.2
Nuke	11	36%	0.81	13.0
Cache	5	40%	0.91	15.0
Anubis	4	50%	0.82	10.8
Overpass	3	33%	1.00	18.0
Mirage	2	50%	1.22	19.5
Vertigo	1	0%	0.53	10.0

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.

13.7%Headshot accuracy

36.5%Accuracy (enemy spotted)

38.9%Spray accuracy

77.8%Counter-strafing

8.6°Preaim

549msReaction time

29.3%T opening success

33.8%CT opening success

0.28Enemies flashed / flash

0.6%Flash assists

7.52HE damage / grenade

2.33Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 13.6725% — below the 15% mark we flag
Aim Training →
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 0.2792 — 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 29.2668% — below the 40% mark we flag

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.

48% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	4–13	-0.04	2%	30 Aug →
nuke	5–13	-0.04	14%	29 Aug →
ancient	6–13	0.04	10%	29 Aug →
cache	13–11	-0.02	11%	23 Aug →
inferno	9–13	-0.06	14%	23 Aug →
nuke	13–7	0.02	28%	23 Aug →
ancient	13–7	-0.07	4%	23 Aug →
office	0–13	-0.06	0%	23 Aug →
inferno	22–20	-0.02	7%	16 Aug →
nuke	13–9	-0.04	14%	15 Aug →
inferno	8–13	-0.09	13%	9 Aug →
cache	4–13	-0.06	27%	9 Aug →
vertigo	11–13	-0.05	7%	9 Aug →
ancient	3–13	-0.01	12%	9 Aug →
inferno	13–11	0.01	13%	9 Aug →
office	13–7	0.03	8%	8 Aug →
overpass	7–13	0.05	10%	5 Aug →
mirage	13–7	0.08	8%	27 Jul →
vertigo	9–5	0.00	14%	27 Jul →
inferno	4–9	-0.09	16%	27 Jul →
inferno	4–9	-0.03	23%	27 Jul →
cache	11–13	0.00	17%	27 Jul →
inferno	13–6	0.09	15%	27 Jul →
office	12–12	0.03	18%	20 Jul →
ancient	13–11	-0.04	7%	20 Jul →
nuke	13–8	0.07	16%	19 Jul →
office	9–13	0.01	23%	19 Jul →
cache	13–5	0.06	24%	19 Jul →
inferno	8–13	-0.01	29%	19 Jul →
ancient	1–13	-0.03	14%	18 Jul →
mirage	2–13	-0.06	21%	18 Jul →
inferno	13–11	0.00	12%	18 Jul →
nuke	10–13	0.02	18%	18 Jul →
ancient	13–5	0.00	12%	18 Jul →
anubis	13–4	0.04	10%	18 Jul →
nuke	6–13	0.00	22%	18 Jul →
mirage	13–8	0.03	18%	17 Jul →
ancient	7–13	-0.07	9%	17 Jul →
ancient	11–13	-0.01	14%	17 Jul →
cache	5–13	-0.02	16%	17 Jul →
inferno	13–2	0.08	17%	17 Jul →
mirage	13–4	-0.01	10%	16 Jul →
vertigo	7–9	-0.01	14%	16 Jul →
anubis	11–13	-0.03	13%	16 Jul →
anubis	13–9	-0.00	21%	15 Jul →
nuke	13–8	0.07	15%	15 Jul →
train	13–6	0.02	13%	15 Jul →
inferno	16–13	0.04	13%	15 Jul →
ancient	13–7	0.10	20%	15 Jul →
nuke	15–15	-0.00	11%	15 Jul →
dust2	12–12	0.02	9%	15 Jul →
cache	10–1	0.02	15%	14 Jul →
inferno	13–5	-0.02	21%	14 Jul →
office	13–8	0.03	24%	14 Jul →
inferno	8–8	0.02	13%	13 Jul →
inferno	13–7	0.02	28%	13 Jul →
vertigo	13–10	0.06	20%	13 Jul →
boulder	11–13	-0.03	23%	13 Jul →
office	13–6	-0.06	29%	13 Jul →
nuke	13–6	0.05	15%	28 Jun →
ancient	13–7	0.03	20%	28 Jun →
mirage	13–9	0.08	14%	28 Jun →
nuke	9–13	-0.01	19%	28 Jun →
inferno	13–16	0.01	13%	28 Jun →
italy	7–13	0.02	13%	27 Jun →
vertigo	13–6	0.04	15%	27 Jun →
inferno	4–9	-0.19	15%	26 Jun →
nuke	8–13	-0.03	9%	25 Jun →
overpass	10–13	0.02	16%	24 Jun →
ancient	13–10	-0.02	14%	24 Jun →
dust2	3–13	-0.03	50%	24 Jun →
anubis	13–11	0.01	16%	24 Jun →
nuke	7–2	-0.04	0%	24 Jun →
inferno	6–13	0.02	10%	24 Jun →
nuke	13–11	-0.02	4%	23 Jun →
mirage	13–9	-0.08	43%	23 Jun →
office	12–12	0.01	27%	23 Jun →
inferno	13–4	0.05	26%	22 Jun →
nuke	8–13	-0.00	7%	22 Jun →
ancient	13–9	0.00	12%	22 Jun →
mirage	2–13	0.02	16%	21 Jun →
inferno	12–12	0.05	13%	21 Jun →
mirage	6–13	-0.09	12%	21 Jun →
nuke	13–8	0.03	22%	21 Jun →
office	8–13	-0.06	22%	21 Jun →
anubis	9–13	-0.01	15%	21 Jun →
mirage	11–13	-0.06	7%	18 Jun →
anubis	0–5	-0.03	100%	18 Jun →
nuke	13–3	0.13	10%	17 Jun →
train	13–4	0.09	14%	17 Jun →
office	12–12	-0.08	38%	16 Jun →
office	13–0	0.03	4%	15 Jun →
ancient	13–4	-0.02	8%	15 Jun →
train	7–12	0.04	16%	15 Jun →
dust2	9–13	0.04	26%	14 Jun →
mirage	13–10	0.03	14%	14 Jun →
mirage	13–7	0.01	16%	14 Jun →
alpine	13–6	0.15	18%	14 Jun →
inferno	16–13	0.01	24%	14 Jun →
inferno	5–13	0.01	17%	14 Jun →