Rusty — CS2 Stats

US76561198159542197[U:1:199276469]Steam profile ↗✓ No bans

2,072Tracked matches58%Win rate2020Tracked since

CSDB Rating6.7 SolidAggressive Rifler

FaceitLevel 5Top 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim84

Positioning53

Utility51

0–100 skill scores via Leetify.

Recent form

HOT47–43–10Last 10047%Win rateWWLWWLLWWW

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

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim8.4

Aggression8.5

Utility5.1

Positioning5.3

Opening Duels3.4

Clutch0.0

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

Plays most like b1t 92% playstyle similarity

Most alike: opening-duel success, 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

Areas to improve

Positioning. Positioning trails aim by 30 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.

T-side openings. Opening success drops from 52% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 585ms 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

Aim8.4

Positioning5.3

Utility5.1

Mechanics8.7

Opening Duels3.4

Win Impact7.6

Composite 6.7/10 (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 0.02 → last ⅓ avg 0.01

Reaction time599ms+15ms

first ⅓ avg 584ms → last ⅓ avg 599ms

Headshot accuracy27.9%+2.9%

first ⅓ avg 24.9% → last ⅓ avg 27.9%

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 13–6

13–2Biggest win — mirage

6Longest win streak

W2Current streak

5–8In matches decided by ≤2 rounds

8Overtime games

Map breakdown

infernoBest map · 60% over 10anubisWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	37	19–18	51%	0.01
mirage	B	24	11–13	46%	0.02
nuke	D	11	3–8	27%	0.01
inferno	A	10	6–4	60%	0.01
cache	B	8	4–4	50%	-0.00
anubis	D	5	1–4	20%	-0.01
overpass	—	3	1–2	33%	-0.00
ancient	—	2	2–0	100%	0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

94Matches

53%Win rate

1.21Avg K/D

92.2ADR

46%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

5Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	6	67%	1.10	15.0
Inferno	3	67%	1.09	18.0
Nuke	2	50%	1.10	17.0
Overpass	1	0%	1.20	18.0
Vertigo	1	100%	0.70	14.0
Anubis	1	0%	1.11	20.0

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.

28.0%Headshot accuracy

34.0%Accuracy (enemy spotted)

34.1%Spray accuracy

89.0%Counter-strafing

9.6°Preaim

585msReaction time

35.3%T opening success

51.6%CT opening success

0.73Enemies flashed / flash

4.0%Flash assists

7.06HE damage / grenade

6.46Flashes / 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.

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 35.2688% — below the 40% mark we flag

Spend your practice time on Anubis

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	16–12	0.00	16%	18 Aug →
ancient	13–7	0.04	27%	18 Aug →
mirage	9–13	0.06	41%	18 Aug →
cache	10–1	-0.03	31%	18 Aug →
dust2	13–11	-0.01	22%	1 Aug →
nuke	3–13	-0.02	24%	28 Jul →
nuke	8–13	-0.03	15%	28 Jul →
mirage	13–8	0.06	19%	24 Jul →
nuke	13–8	0.08	26%	24 Jul →
inferno	13–8	0.05	24%	24 Jul →
nuke	5–13	0.09	33%	23 Jul →
dust2	5–13	0.01	27%	23 Jul →
dust2	6–13	-0.02	23%	17 Jul →
dust2	11–13	0.01	19%	17 Jul →
dust2	7–13	-0.01	37%	17 Jul →
dust2	13–3	0.02	45%	11 Jul →
dust2	11–2	-0.02	19%	3 Jul →
dust2	11–13	0.04	27%	3 Jul →
mirage	12–12	0.05	21%	3 Jul →
dust2	7–13	-0.03	38%	3 Jul →
dust2	12–12	0.03	35%	2 Jul →
mirage	13–8	-0.05	30%	2 Jul →
mirage	12–12	0.06	28%	2 Jul →
dust2	13–10	0.02	24%	27 Jun →
dust2	13–7	0.01	25%	19 Jun →
dust2	11–13	0.02	16%	19 Jun →
dust2	13–5	0.00	30%	19 Jun →
dust2	13–6	0.06	12%	18 Jun →
mirage	12–12	-0.04	75%	18 Jun →
dust2	13–9	0.04	34%	18 Jun →
dust2	2–13	-0.05	31%	29 May →
dust2	12–12	0.03	22%	28 May →
dust2	3–13	-0.01	26%	28 May →
dust2	2–13	-0.02	24%	28 May →
inferno	13–11	0.00	29%	28 May →
dust2	13–10	0.04	40%	22 May →
cache	9–13	0.01	24%	22 May →
nuke	11–13	-0.00	45%	21 May →
dust2	13–6	0.16	39%	21 May →
mirage	13–8	0.02	16%	19 May →
cache	10–13	0.01	33%	15 May →
cache	1–13	-0.06	27%	15 May →
cache	13–10	0.06	50%	15 May →
dust2	2–13	-0.01	25%	15 May →
dust2	13–8	0.07	36%	6 May →
cache	13–5	-0.04	34%	5 May →
cache	9–13	-0.07	30%	5 May →
cache	13–3	0.11	30%	5 May →
nuke	13–11	0.01	38%	25 Apr →
mirage	7–13	0.06	15%	25 Apr →
dust2	3–13	-0.07	33%	11 Apr →
mirage	5–13	-0.04	20%	11 Apr →
nuke	11–13	-0.03	15%	30 Mar →
dust2	8–13	-0.04	32%	29 Mar →
nuke	15–15	-0.03	19%	29 Mar →
mirage	7–13	-0.05	16%	27 Mar →
mirage	2–6	-0.04	5%	20 Mar →
mirage	10–13	0.02	19%	20 Mar →
dust2	15–15	-0.05	29%	7 Mar →
mirage	13–6	-0.00	20%	7 Mar →
ancient	13–6	-0.03	16%	7 Mar →
nuke	13–7	0.05	29%	7 Mar →
mirage	12–16	0.02	22%	5 Mar →
dust2	13–10	0.04	18%	4 Mar →
mirage	2–13	-0.03	25%	4 Mar →
mirage	13–6	0.01	24%	28 Feb →
dust2	9–13	-0.03	20%	28 Feb →
mirage	13–9	0.13	25%	28 Feb →
nuke	7–13	-0.03	17%	28 Feb →
mirage	13–7	0.05	29%	28 Feb →
inferno	11–13	0.03	50%	28 Feb →
mirage	13–4	-0.03	25%	28 Feb →
anubis	13–9	0.01	12%	27 Feb →
mirage	11–13	0.04	29%	27 Feb →
mirage	13–2	0.14	57%	27 Feb →
inferno	15–15	-0.01	19%	24 Feb →
inferno	9–13	-0.02	23%	24 Feb →
anubis	10–13	0.02	27%	24 Feb →
dust2	13–11	0.05	24%	21 Feb →
nuke	9–13	-0.02	36%	21 Feb →
mirage	9–13	0.01	14%	21 Feb →
dust2	13–10	-0.05	33%	21 Feb →
overpass	3–13	-0.01	21%	21 Feb →
inferno	13–7	0.03	26%	21 Feb →
anubis	10–13	-0.04	11%	21 Feb →
overpass	13–2	0.03	15%	14 Feb →
anubis	11–13	-0.02	25%	14 Feb →
mirage	13–10	0.00	19%	14 Feb →
inferno	2–13	-0.03	14%	14 Feb →
dust2	15–15	0.08	24%	14 Feb →
mirage	16–12	0.00	16%	13 Feb →
inferno	13–8	0.04	18%	13 Feb →
anubis	4–13	-0.03	40%	13 Feb →
dust2	13–8	0.01	25%	12 Feb →
dust2	13–6	0.04	18%	10 Feb →
dust2	13–8	-0.01	19%	10 Feb →
dust2	13–11	0.07	55%	8 Feb →
inferno	13–8	0.03	29%	8 Feb →
dust2	13–9	0.05	9%	8 Feb →
overpass	15–15	-0.03	17%	3 Feb →