Foxy! — CS2 Stats

76561197972912747[U:1:12647019]

1,946Tracked matches48%Win rate2020Tracked since

CSDB Rating4.6 Developing

Premier CS Rating10,462Blue band · top ~52.5% of ranked players (population est.)

CSDB Leaderboard#13559 of 18579 tracked

FaceitLevel 7 · 1,396 ELOTop 42.3% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim50

Positioning46

Utility65

0–100 skill scores via Leetify.

Recent form

STEADY43–52–5Last 10043%Win rateLWLWLWLWTT

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

Player DNA

Aim5.0

Aggression5.3

Utility6.5

Positioning4.6

Opening Duels1.3

Clutch2.8

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 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

Reaction time. 581ms 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

Aim5.0

Positioning4.6

Utility6.5

Mechanics5.7

Opening Duels1.3

Win Impact4.4

Composite 4.6/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.00

first ⅓ avg -0.00 → last ⅓ avg -0.01

Reaction time589ms−20ms

first ⅓ avg 609ms → last ⅓ avg 589ms

Headshot accuracy15.6%−3.0%

first ⅓ avg 18.7% → last ⅓ avg 15.6%

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

0.20Best rating — dust2 13–1

13–1Biggest win — ancient

4Longest win streak

6–7In matches decided by ≤2 rounds

5Overtime games

Map breakdown

nukeBest map · 53% over 15anubisWeakest map · 22% over 9

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	15	7–8	47%	0.00
nuke	B	15	8–7	53%	-0.00
mirage	B	15	8–7	53%	0.01
dust2	C	14	6–8	43%	0.01
inferno	C	11	4–7	36%	0.00
anubis	D	9	2–7	22%	-0.03
cache	C	9	4–5	44%	-0.03
overpass	—	3	1–2	33%	-0.04
fachwerk	—	2	0–2	0%	-0.05
vertigo	—	2	0–2	0%	-0.04
boulder	—	1	0–1	0%	-0.01
shelter	—	1	1–0	100%	0.02
train	—	1	1–0	100%	-0.02
sanctum	—	1	0–1	0%	-0.04
poseidon	—	1	1–0	100%	0.05

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

433Matches

53%Win rate

1.00Avg K/D

77.9ADR

39%Headshot %

Clutches & streaks

34%1v1 clutch win

15%1v2 clutch win

6Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	45	60%	0.93	14.6
Ancient	35	46%	1.00	15.3
Nuke	26	77%	0.99	15.3
Mirage	24	54%	0.89	12.0
Dust2	23	39%	0.91	14.2
Anubis	9	44%	0.85	13.7
Overpass	8	38%	0.98	14.1
Vertigo	4	25%	1.03	11.5

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.

16.2%Headshot accuracy

31.6%Accuracy (enemy spotted)

31.1%Spray accuracy

75.6%Counter-strafing

11.5°Preaim

581msReaction time

34.2%T opening success

36.0%CT opening success

0.60Enemies flashed / flash

6.6%Flash assists

15.26HE damage / grenade

8.62Flashes / 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 34.2368% — 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.

22% win rate across 9 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
ancient	3–13	0.03	12%	17 Aug →
nuke	13–5	0.06	18%	16 Aug →
fachwerk	8–13	-0.05	35%	15 Aug →
inferno	13–8	0.02	12%	15 Aug →
overpass	5–13	-0.08	26%	15 Aug →
ancient	13–8	0.02	17%	15 Aug →
boulder	5–13	-0.01	8%	12 Aug →
shelter	13–8	0.02	13%	12 Aug →
dust2	15–15	0.02	17%	9 Aug →
fachwerk	12–12	-0.06	30%	8 Aug →
ancient	13–1	0.02	15%	8 Aug →
anubis	13–5	0.05	17%	8 Aug →
inferno	13–5	-0.00	16%	8 Aug →
dust2	13–7	-0.01	13%	8 Aug →
cache	3–13	-0.04	19%	8 Aug →
dust2	13–10	-0.00	19%	2 Aug →
inferno	15–15	0.04	17%	2 Aug →
nuke	11–13	-0.03	13%	2 Aug →
anubis	0–6	-0.08	0%	2 Aug →
vertigo	7–13	-0.08	10%	2 Aug →
ancient	13–6	0.10	17%	2 Aug →
anubis	13–4	-0.01	12%	1 Aug →
cache	7–13	-0.06	31%	1 Aug →
inferno	16–14	0.02	10%	1 Aug →
ancient	10–13	-0.09	11%	27 Jul →
mirage	10–13	0.14	13%	27 Jul →
mirage	11–13	-0.01	14%	27 Jul →
dust2	13–4	0.04	5%	26 Jul →
ancient	6–13	-0.09	18%	26 Jul →
cache	5–13	-0.07	17%	26 Jul →
dust2	10–13	-0.01	15%	26 Jul →
mirage	13–9	-0.03	13%	18 Jul →
cache	3–13	-0.01	16%	18 Jul →
nuke	7–13	-0.07	17%	18 Jul →
mirage	13–11	0.02	10%	12 Jul →
anubis	4–13	-0.05	3%	12 Jul →
inferno	13–10	0.01	13%	27 May →
nuke	13–4	0.13	20%	27 May →
mirage	13–6	0.00	15%	27 May →
dust2	9–13	-0.06	19%	26 May →
dust2	10–13	-0.02	15%	25 May →
mirage	13–4	0.02	12%	25 May →
inferno	9–13	0.08	16%	22 May →
mirage	10–13	0.00	14%	22 May →
ancient	13–11	0.03	14%	18 May →
mirage	16–13	0.03	12%	17 May →
anubis	6–13	-0.04	13%	17 May →
nuke	7–13	-0.02	14%	17 May →
mirage	6–12	0.05	17%	17 May →
ancient	5–13	-0.12	15%	17 May →
cache	13–9	-0.01	20%	15 May →
nuke	3–9	-0.10	11%	11 May →
cache	13–4	0.03	15%	10 May →
cache	13–6	0.00	10%	5 May →
overpass	4–13	-0.07	6%	5 May →
ancient	13–9	0.07	16%	5 May →
dust2	13–7	0.04	13%	4 May →
overpass	13–11	0.04	21%	4 May →
cache	9–13	-0.07	15%	29 Apr →
cache	13–6	-0.05	17%	29 Apr →
nuke	12–12	0.00	16%	26 Apr →
train	13–11	-0.02	13%	26 Apr →
inferno	5–13	-0.04	26%	26 Apr →
nuke	9–13	0.02	8%	24 Apr →
nuke	13–6	0.06	11%	24 Apr →
inferno	6–13	-0.01	14%	22 Apr →
nuke	13–7	-0.10	14%	22 Apr →
dust2	13–6	-0.01	20%	22 Apr →
sanctum	6–9	-0.04	16%	19 Apr →
poseidon	9–4	0.05	27%	19 Apr →
ancient	13–4	0.05	19%	19 Apr →
inferno	6–13	-0.04	14%	18 Apr →
nuke	13–4	-0.05	15%	18 Apr →
ancient	4–13	-0.07	15%	18 Apr →
dust2	4–13	-0.07	13%	15 Apr →
inferno	6–13	-0.02	19%	15 Apr →
nuke	13–7	0.04	26%	12 Apr →
dust2	11–13	0.01	18%	12 Apr →
inferno	3–13	-0.05	6%	12 Apr →
dust2	11–13	-0.06	23%	11 Apr →
mirage	5–13	-0.07	12%	11 Apr →
vertigo	4–13	-0.00	27%	11 Apr →
ancient	4–13	0.02	9%	6 Apr →
anubis	5–13	-0.08	14%	6 Apr →
mirage	13–6	-0.01	26%	6 Apr →
ancient	15–15	0.05	9%	6 Apr →
ancient	13–4	0.05	22%	6 Apr →
mirage	13–5	-0.01	12%	30 Mar →
mirage	13–2	0.01	24%	30 Mar →
mirage	4–13	-0.01	33%	30 Mar →
nuke	13–11	-0.04	23%	30 Mar →
anubis	8–13	-0.04	15%	28 Mar →
dust2	11–13	0.11	27%	28 Mar →
mirage	11–13	-0.04	13%	24 Mar →
nuke	13–5	0.10	17%	24 Mar →
ancient	10–13	-0.05	14%	24 Mar →
anubis	6–13	-0.03	13%	24 Mar →
anubis	11–13	-0.02	23%	22 Mar →
dust2	13–1	0.20	31%	22 Mar →
nuke	8–13	-0.01	21%	22 Mar →