thoinkiee — CS2 Stats

76561198106472271[U:1:146206543]

746Tracked matches48%Win rate2020Tracked since

CSDB Rating5.8 SolidPassive Rifler

FaceitLevel 6Top 54.0% of ranked FACEIT players

WingmanGold Nova II

Ladder ranks via Leetify

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Performance scores

Aim72

Positioning45

Utility46

0–100 skill scores via Leetify.

Recent form

STEADY45–48–7Last 10045%Win rateLLWLWLWLWW

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

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

Aim7.2

Aggression3.1

Utility4.6

Positioning4.5

Opening Duels0.0

Clutch3.6

Excellent counter-strafingStrong CT-side opener

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 82% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

Where you differ: lower opening-duel success; 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

Strengths

Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

T-side openings. Opening success drops from 45% on CT to 13% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 614ms 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

Aim7.2

Positioning4.5

Utility4.6

Mechanics9.2

Opening Duels1.9

Win Impact4.4

Composite 5.8/10 (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 rating-0.01−0.01

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time621ms−4ms

first ⅓ avg 624ms → last ⅓ avg 621ms

Headshot accuracy21.5%−2.6%

first ⅓ avg 24.1% → last ⅓ avg 21.5%

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

0.12Best rating — cache 9–0

13–1Biggest win — cache

6Longest win streak

L2Current streak

15–7In matches decided by ≤2 rounds

19Overtime games

Map breakdown

mirageBest map · 64% over 22infernoWeakest map · 32% over 22

Map	Grade	Played	Record	Win rate	Avg rating
inferno	D	22	7–15	32%	0.00
mirage	A	22	14–8	64%	-0.01
ancient	B	19	10–9	53%	-0.00
dust2	C	12	5–7	42%	-0.01
cache	B	10	5–5	50%	0.02
nuke	C	10	4–6	40%	0.01
vertigo	—	2	0–2	0%	-0.19
overpass	—	2	0–2	0%	-0.04
train	—	1	0–1	0%	-0.08

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (32% over 22). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

57Matches

44%Win rate

1.00Avg K/D

84.1ADR

52%Headshot %

Clutches & streaks

38%1v1 clutch win

25%1v2 clutch win

5Longest win streak

Recent Faceit resultsWLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	15	47%	1.06	15.5
Inferno	9	33%	0.89	15.0
Anubis	8	38%	1.04	13.6
Ancient	6	50%	1.15	18.2
Nuke	5	60%	1.26	17.0
Dust2	2	50%	0.85	17.0
Vertigo	2	100%	1.46	24.0

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.

22.0%Headshot accuracy

30.9%Accuracy (enemy spotted)

31.9%Spray accuracy

91.3%Counter-strafing

9.6°Preaim

614msReaction time

13.2%T opening success

45.1%CT opening success

0.54Enemies flashed / flash

8.4%Flash assists

8.33HE damage / grenade

9.59Flashes / 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 13.19% — 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.

32% win rate across 22 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
dust2	12–16	-0.05	30%	24 Aug →
inferno	11–13	-0.04	16%	20 Aug →
cache	13–1	0.02	24%	13 Aug →
cache	12–16	-0.04	19%	13 Aug →
mirage	16–12	-0.00	18%	13 Aug →
ancient	9–13	0.00	23%	12 Aug →
mirage	13–11	0.02	13%	10 Aug →
dust2	5–13	-0.04	30%	9 Aug →
cache	13–11	-0.01	22%	7 Aug →
cache	9–0	0.12	25%	6 Aug →
ancient	13–3	0.10	23%	6 Aug →
cache	9–13	0.01	18%	2 Aug →
nuke	13–8	-0.01	24%	2 Aug →
mirage	13–11	0.02	20%	31 May →
cache	13–3	0.11	30%	31 May →
cache	9–13	-0.04	20%	31 May →
cache	10–13	-0.01	19%	28 May →
cache	12–12	-0.01	21%	8 May →
cache	13–7	0.05	17%	7 May →
nuke	10–13	-0.03	14%	13 Jan →
nuke	8–8	0.09	21%	11 Jan →
vertigo	2–9	-0.28	14%	11 Jan →
inferno	5–9	-0.10	11%	11 Jan →
ancient	13–2	0.02	22%	11 Jan →
train	11–13	-0.08	23%	10 Jan →
nuke	10–13	-0.02	18%	10 Jan →
inferno	6–13	-0.07	13%	10 Jan →
mirage	13–11	0.02	26%	6 Jan →
ancient	2–6	-0.05	21%	6 Jan →
inferno	10–13	0.00	44%	6 Jan →
mirage	9–13	0.07	28%	5 Jan →
ancient	13–5	-0.02	13%	30 Dec →
ancient	13–9	-0.02	30%	14 Dec →
inferno	8–13	-0.02	20%	1 Dec →
overpass	6–13	-0.04	23%	1 Dec →
inferno	11–13	0.01	34%	25 Nov →
dust2	6–13	-0.10	35%	25 Nov →
dust2	13–11	0.05	32%	25 Nov →
nuke	13–16	-0.05	29%	25 Nov →
ancient	13–10	-0.02	14%	25 Nov →
dust2	5–13	-0.09	13%	15 Nov →
inferno	4–13	-0.03	19%	15 Nov →
ancient	13–6	-0.02	22%	14 Nov →
mirage	16–14	0.00	19%	9 Nov →
ancient	16–14	0.05	33%	9 Nov →
nuke	16–14	-0.04	30%	8 Nov →
mirage	13–10	-0.09	15%	25 Oct →
mirage	13–11	0.03	13%	25 Oct →
nuke	10–13	-0.02	28%	25 Oct →
inferno	10–13	-0.02	30%	13 Oct →
mirage	16–13	-0.03	13%	13 Oct →
ancient	10–13	-0.11	41%	8 Oct →
mirage	13–6	-0.06	17%	6 Oct →
mirage	10–13	-0.00	25%	4 Oct →
inferno	5–13	-0.02	16%	3 Oct →
dust2	16–13	-0.00	18%	3 Oct →
inferno	15–15	0.02	16%	1 Oct →
mirage	15–15	0.06	29%	1 Oct →
inferno	11–13	0.05	24%	26 Sept →
nuke	4–13	0.02	28%	26 Sept →
mirage	13–11	0.03	18%	26 Sept →
ancient	5–13	-0.03	11%	21 Sept →
inferno	5–13	-0.03	27%	21 Sept →
dust2	9–13	0.01	28%	21 Sept →
ancient	13–6	0.04	43%	21 Sept →
nuke	13–9	0.04	18%	21 Sept →
mirage	13–8	-0.02	30%	21 Sept →
inferno	10–13	0.03	32%	21 Sept →
mirage	13–11	0.02	27%	19 Sept →
ancient	13–8	0.03	14%	19 Sept →
vertigo	5–9	-0.11	13%	14 Sept →
dust2	3–13	-0.05	16%	13 Sept →
ancient	15–15	0.01	33%	13 Sept →
inferno	7–13	0.02	24%	5 Sept →
ancient	14–16	0.03	35%	24 Aug →
inferno	13–8	0.05	35%	24 Aug →
inferno	13–11	0.01	22%	24 Aug →
dust2	16–14	0.00	22%	24 Aug →
ancient	11–13	0.01	18%	18 Aug →
dust2	13–6	0.02	26%	18 Aug →
inferno	13–1	0.01	38%	18 Aug →
mirage	11–13	-0.01	23%	18 Aug →
inferno	13–9	0.02	23%	15 Aug →
inferno	15–15	0.07	17%	15 Aug →
overpass	10–13	-0.04	16%	15 Aug →
inferno	10–3	0.06	28%	15 Aug →
nuke	11–5	0.10	32%	15 Aug →
mirage	1–13	-0.09	27%	15 Aug →
ancient	16–14	0.00	24%	15 Aug →
mirage	13–1	0.01	25%	15 Aug →
ancient	5–13	-0.03	32%	12 Aug →
mirage	9–13	-0.01	15%	12 Aug →
mirage	15–15	0.01	14%	11 Aug →
dust2	13–8	0.03	40%	11 Aug →
mirage	7–13	-0.06	24%	11 Aug →
dust2	8–13	0.12	21%	11 Aug →
ancient	4–13	-0.07	28%	11 Aug →
mirage	16–13	-0.02	9%	11 Aug →
inferno	13–6	0.00	22%	10 Aug →
inferno	16–14	0.03	19%	10 Aug →