Felix el Gato guapo — CS2 Stats

76561198241061466[U:1:280795738]

3,929Tracked matches52%Win rate2020Tracked since

CSDB Rating3.6 Learning

Premier CS Rating15,865Purple band · top ~25% of ranked players (population est.)

WingmanGold Nova Master

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim34

Positioning31

Utility52

0–100 skill scores via Leetify.

Recent form

STEADY52–47–1Last 10052%Win rateLWLLLLWWLW

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Aim3.4

Aggression2.4

Utility5.2

Positioning3.1

Opening Duels0.0

Clutch3.2

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 75% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

T-side openings. Opening success drops from 36% on CT to 19% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 595ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

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

Aim3.4

Positioning3.1

Utility5.2

Mechanics3.6

Opening Duels0.7

Win Impact5.6

Composite 3.6/10 (Learning), 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 rating-0.03−0.03

first ⅓ avg -0.01 → last ⅓ avg -0.03

Reaction time605ms+62ms

first ⅓ avg 543ms → last ⅓ avg 605ms

Headshot accuracy12.8%−0.9%

first ⅓ avg 13.7% → last ⅓ avg 12.8%

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

0.12Best rating — inferno 9–3

13–0Biggest win — anubis

10Longest win streak

12–5In matches decided by ≤2 rounds

7Overtime games

Map breakdown

anubisBest map · 61% over 18ancientWeakest map · 47% over 19

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	33	16–17	48%	-0.01
inferno	A	21	12–9	57%	-0.03
ancient	B	19	9–10	47%	-0.03
anubis	A	18	11–7	61%	-0.01
dust2	A	7	4–3	57%	-0.05
cache	—	2	0–2	0%	-0.07

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (47% over 19). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

544Matches

50%Win rate

0.75Avg K/D

65.4ADR

40%Headshot %

Clutches & streaks

36%1v1 clutch win

17%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	139	53%	0.81	12.0
Dust2	111	53%	0.70	11.1
Ancient	110	49%	0.74	11.7
Inferno	102	46%	0.72	11.6
Anubis	63	48%	0.74	11.9
Nuke	6	17%	0.73	11.2
Cache	5	40%	1.16	16.2
Train	5	60%	0.93	18.0

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.

12.8%Headshot accuracy

30.8%Accuracy (enemy spotted)

36.8%Spray accuracy

66.1%Counter-strafing

13.2°Preaim

595msReaction time

19.0%T opening success

35.8%CT opening success

0.56Enemies flashed / flash

3.5%Flash assists

8.15HE damage / grenade

6.65Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.2161° — above the 12° mark we flag
Aim Training →
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 12.7847% — below the 15% mark we flag
Aim Training →

Spend your practice time on Ancient

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

47% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	5–13	-0.09	11%	24 Aug →
mirage	13–10	0.08	11%	23 Aug →
anubis	6–13	-0.04	15%	22 Aug →
dust2	3–13	-0.06	7%	22 Aug →
mirage	4–13	0.04	17%	22 Aug →
ancient	4–13	-0.08	15%	21 Aug →
ancient	13–8	-0.09	10%	21 Aug →
mirage	13–11	0.03	14%	18 Aug →
mirage	8–13	-0.06	5%	17 Aug →
ancient	13–8	-0.03	17%	17 Aug →
inferno	11–13	-0.07	12%	15 Aug →
mirage	13–8	0.03	9%	15 Aug →
ancient	15–15	-0.03	14%	15 Aug →
ancient	3–13	-0.01	11%	10 Aug →
ancient	13–11	0.03	24%	9 Aug →
mirage	13–10	0.04	14%	9 Aug →
inferno	11–13	-0.05	14%	7 Aug →
anubis	13–5	-0.01	26%	7 Aug →
mirage	6–13	-0.01	5%	7 Aug →
inferno	4–13	-0.06	14%	7 Aug →
ancient	13–8	-0.05	21%	7 Aug →
inferno	13–11	-0.05	10%	5 Aug →
mirage	13–9	-0.04	13%	5 Aug →
inferno	5–13	-0.06	11%	4 Aug →
ancient	6–13	-0.05	7%	4 Aug →
dust2	11–13	-0.11	8%	4 Aug →
ancient	16–14	-0.08	3%	31 Jul →
mirage	13–11	-0.00	12%	26 Jul →
inferno	13–10	-0.03	13%	26 Jul →
anubis	13–4	0.02	25%	26 Jul →
anubis	3–13	-0.04	5%	26 Jul →
inferno	9–13	-0.06	17%	25 Jul →
mirage	8–13	-0.08	10%	25 Jul →
ancient	13–7	0.03	19%	21 Jul →
mirage	13–8	0.08	22%	21 Jul →
anubis	3–13	-0.06	9%	19 Jul →
mirage	13–2	0.03	12%	19 Jul →
inferno	13–5	-0.03	15%	19 Jul →
dust2	13–5	-0.01	27%	19 Jul →
anubis	11–13	-0.03	13%	15 Jul →
ancient	9–13	-0.04	11%	15 Jul →
mirage	0–7	-0.05	8%	15 Jul →
cache	8–13	-0.07	22%	13 Jul →
mirage	14–16	-0.02	19%	13 Jul →
anubis	13–10	-0.06	11%	13 Jul →
anubis	13–4	-0.01	23%	13 Jul →
mirage	13–3	0.01	16%	13 Jul →
mirage	8–13	-0.05	22%	12 Jul →
ancient	13–6	-0.02	15%	12 Jul →
ancient	6–13	-0.05	8%	12 Jul →
cache	6–13	-0.07	8%	12 Jul →
mirage	13–6	0.06	11%	6 Jul →
mirage	8–13	-0.03	20%	3 Jul →
anubis	13–9	-0.01	13%	1 Jul →
mirage	8–13	-0.07	13%	30 Jun →
mirage	1–13	-0.09	16%	28 Jun →
anubis	13–0	0.02	15%	28 Jun →
anubis	4–13	-0.03	12%	25 Jun →
dust2	4–13	-0.13	18%	24 Jun →
anubis	13–7	0.08	13%	23 Jun →
inferno	9–7	-0.06	14%	23 Jun →
inferno	9–3	0.12	8%	21 Jun →
inferno	9–7	-0.13	9%	21 Jun →
ancient	16–13	-0.01	18%	13 Jun →
anubis	13–11	-0.05	11%	13 Jun →
mirage	16–14	-0.04	15%	11 Jun →
ancient	10–13	-0.03	10%	8 Jun →
inferno	13–5	0.03	17%	7 Jun →
dust2	13–0	0.00	0%	7 Jun →
dust2	13–9	-0.03	20%	7 Jun →
inferno	13–11	-0.06	15%	6 Jun →
inferno	16–14	0.04	22%	6 Jun →
dust2	13–10	-0.02	22%	6 Jun →
mirage	13–3	0.02	11%	4 Jun →
mirage	13–5	0.07	11%	3 Jun →
inferno	13–7	0.02	15%	2 Jun →
mirage	13–5	-0.06	7%	2 Jun →
anubis	13–16	-0.04	12%	1 Jun →
mirage	5–13	0.00	14%	1 Jun →
ancient	5–13	0.01	9%	1 Jun →
mirage	4–13	-0.05	11%	1 Jun →
mirage	13–6	0.12	11%	1 Jun →
mirage	9–13	-0.03	30%	31 May →
inferno	5–13	-0.00	18%	31 May →
mirage	9–13	-0.02	19%	31 May →
mirage	13–6	-0.02	12%	30 May →
anubis	13–7	0.05	13%	30 May →
inferno	5–13	-0.04	16%	29 May →
mirage	0–3	-0.02	0%	28 May →
inferno	7–13	-0.06	9%	28 May →
anubis	13–8	0.05	14%	27 May →
ancient	5–13	-0.08	15%	27 May →
anubis	13–3	0.05	7%	27 May →
anubis	5–13	-0.03	4%	27 May →
ancient	13–11	0.09	16%	24 May →
mirage	7–13	-0.02	28%	22 May →
inferno	5–13	-0.05	12%	21 May →
mirage	4–13	-0.02	16%	21 May →
inferno	13–10	-0.07	7%	20 May →
inferno	13–9	-0.03	20%	20 May →