AimhoT — CS2 Stats

76561197960353379[U:1:87651]Steam profile ↗

1,936Tracked matches53%Win rate2020Tracked since

CSDB Rating4.7 DevelopingSupport

FaceitLevel 5 · 1,199 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning42

Utility77

0–100 skill scores via Leetify.

Recent form

STEADY49–50–1Last 10049%Win rateWWLLWLLWLW

Last 10 vs previous 10: -20pp win rate · +0.04 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim5.2

Aggression4.0

Utility7.7

Positioning4.2

Opening Duels1.6

Clutch1.8

Strong CT-side openerEffective flashesHigh utility contribution

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 83% playstyle similarity

Most alike: opening-duel success, 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

Strengths

Utility. Utility score of 77 — grenade impact well above the norm.

Areas to improve

T-side openings. Opening success drops from 50% on CT to 23% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 660ms 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

Aim5.2

Positioning4.2

Utility7.7

Mechanics5.7

Opening Duels2.5

Win Impact6.1

Composite 4.7/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.01

first ⅓ avg 0.00 → last ⅓ avg -0.01

Reaction time660ms+13ms

first ⅓ avg 647ms → last ⅓ avg 660ms

Headshot accuracy23.2%+2.7%

first ⅓ avg 20.5% → last ⅓ avg 23.2%

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

0.16Best rating — inferno 13–4

13–1Biggest win — nuke

5Longest win streak

W2Current streak

7–10In matches decided by ≤2 rounds

13Overtime games

Map breakdown

ancientBest map · 57% over 14infernoWeakest map · 41% over 29

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	29	12–17	41%	-0.00
nuke	B	23	12–11	52%	-0.01
overpass	B	15	8–7	53%	-0.01
ancient	A	14	8–6	57%	0.01
anubis	B	11	5–6	45%	-0.00
mirage	—	4	1–3	25%	-0.02
dust2	—	4	3–1	75%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (41% over 29). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

239Matches

49%Win rate

1.03Avg K/D

79.0ADR

44%Headshot %

Clutches & streaks

29%1v1 clutch win

19%1v2 clutch win

5Longest win streak

Recent Faceit resultsWLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	9	78%	0.88	12.4
Inferno	5	80%	1.28	19.6
Nuke	4	50%	1.20	18.5
Anubis	3	33%	0.75	13.3
Overpass	2	0%	0.77	11.0
Vertigo	2	50%	0.42	8.0
Cache	1	0%	0.94	15.0
Dust2	1	100%	0.63	12.0

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.

22.3%Headshot accuracy

31.4%Accuracy (enemy spotted)

35.9%Spray accuracy

75.7%Counter-strafing

12.1°Preaim

660msReaction time

23.0%T opening success

49.9%CT opening success

0.72Enemies flashed / flash

14.2%Flash assists

11.24HE damage / grenade

11.01Flashes / 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 12.1003° — above the 12° mark we flag
Aim Training →

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.

41% win rate across 29 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
mirage	13–4	0.04	26%	1 Aug →
dust2	13–2	0.14	21%	1 Aug →
inferno	8–13	0.02	25%	1 Aug →
nuke	10–13	0.01	19%	21 Jul →
ancient	13–4	0.01	69%	21 Jul →
overpass	14–16	-0.03	22%	23 May →
inferno	11–13	-0.01	22%	23 May →
nuke	13–7	0.03	50%	23 May →
overpass	6–13	0.01	24%	17 May →
inferno	16–12	-0.06	19%	17 May →
dust2	13–9	-0.07	9%	15 May →
inferno	10–13	-0.00	23%	15 May →
overpass	13–4	-0.08	0%	15 May →
nuke	13–6	-0.02	24%	3 May →
nuke	13–2	-0.04	28%	3 May →
anubis	13–10	-0.02	19%	3 May →
nuke	13–9	0.01	26%	3 May →
inferno	12–16	-0.06	16%	2 May →
nuke	13–4	0.02	15%	2 May →
inferno	8–13	0.02	20%	19 Apr →
nuke	10–13	-0.02	23%	12 Apr →
dust2	9–13	-0.04	22%	12 Apr →
nuke	9–13	-0.07	24%	10 Apr →
inferno	9–13	-0.02	23%	10 Apr →
dust2	13–10	-0.00	22%	10 Apr →
nuke	13–10	-0.07	13%	10 Apr →
overpass	13–11	0.01	11%	10 Apr →
ancient	7–13	0.03	20%	9 Apr →
inferno	13–4	0.16	27%	9 Apr →
inferno	4–13	-0.04	26%	5 Apr →
nuke	5–13	-0.07	45%	5 Apr →
overpass	5–13	-0.09	11%	5 Apr →
nuke	14–16	-0.02	25%	5 Apr →
inferno	14–16	-0.07	15%	5 Apr →
ancient	2–13	-0.01	15%	5 Apr →
inferno	16–14	-0.00	33%	5 Apr →
inferno	9–13	0.00	17%	4 Apr →
inferno	16–14	-0.02	13%	3 Apr →
inferno	8–13	-0.04	18%	3 Apr →
nuke	13–10	-0.02	15%	3 Apr →
inferno	13–4	0.01	12%	3 Apr →
ancient	13–8	-0.00	23%	3 Apr →
ancient	4–13	-0.04	30%	3 Apr →
inferno	13–16	0.02	21%	2 Apr →
mirage	14–16	-0.01	12%	2 Apr →
inferno	13–11	-0.03	21%	2 Apr →
overpass	14–16	-0.05	16%	2 Apr →
inferno	4–13	-0.07	7%	29 Mar →
ancient	13–9	0.06	11%	28 Mar →
overpass	13–11	-0.02	17%	28 Mar →
overpass	13–5	0.04	11%	28 Mar →
anubis	15–15	-0.01	11%	27 Mar →
overpass	13–8	0.01	8%	27 Mar →
nuke	13–1	0.04	18%	27 Mar →
inferno	13–10	0.09	13%	27 Mar →
mirage	11–13	-0.04	21%	27 Mar →
anubis	14–16	-0.00	13%	26 Mar →
anubis	9–13	-0.04	8%	26 Mar →
ancient	6–13	-0.01	5%	25 Mar →
anubis	13–9	0.03	12%	25 Mar →
nuke	13–11	-0.06	18%	25 Mar →
overpass	13–6	-0.01	32%	24 Mar →
inferno	13–9	0.02	17%	23 Mar →
overpass	10–13	-0.02	14%	23 Mar →
inferno	9–13	-0.03	11%	23 Mar →
overpass	10–13	-0.01	24%	23 Mar →
nuke	10–13	0.00	21%	23 Mar →
inferno	4–13	0.03	20%	23 Mar →
ancient	5–13	-0.03	21%	23 Mar →
anubis	13–4	0.05	16%	22 Mar →
nuke	13–11	-0.04	27%	22 Mar →
inferno	7–13	-0.00	29%	21 Mar →
inferno	13–5	0.02	22%	21 Mar →
inferno	13–8	-0.02	15%	21 Mar →
overpass	10–13	-0.01	20%	21 Mar →
inferno	14–16	0.03	18%	16 Mar →
inferno	10–13	-0.05	18%	15 Mar →
anubis	9–13	-0.10	23%	15 Mar →
overpass	13–7	0.02	40%	15 Mar →
ancient	13–4	0.05	20%	15 Mar →
ancient	13–5	-0.04	8%	15 Mar →
nuke	13–5	0.04	10%	15 Mar →
nuke	10–13	-0.00	19%	15 Mar →
mirage	6–13	-0.07	31%	15 Mar →
ancient	13–3	-0.04	5%	15 Mar →
anubis	13–5	0.01	14%	15 Mar →
inferno	13–7	0.07	30%	14 Mar →
overpass	13–5	0.04	41%	14 Mar →
inferno	13–10	-0.01	27%	14 Mar →
nuke	8–13	-0.02	30%	14 Mar →
nuke	8–13	0.01	22%	14 Mar →
anubis	9–13	-0.00	15%	13 Mar →
ancient	13–8	0.01	21%	13 Mar →
nuke	8–13	-0.04	10%	13 Mar →
nuke	13–10	0.03	19%	13 Mar →
ancient	8–13	-0.03	16%	13 Mar →
ancient	13–4	0.11	16%	13 Mar →
anubis	10–13	0.04	10%	8 Mar →
nuke	11–13	-0.00	32%	8 Mar →
anubis	13–7	-0.01	15%	8 Mar →