HASCHO — CS2 Stats

76561199634009154[U:1:1673743426]✓ No bans

1,960Tracked matches53%Win rate2024Tracked since

CSDB Rating3.7 Learning

Premier CS Rating5,165Light Blue band · top ~78% of ranked players (population est.)

CSDB Leaderboard#9108 of 12016 tracked

FaceitLevel 3 · 828 ELOTop 90.6% of ranked FACEIT players

WingmanMaster Guardian I

Ladder ranks via Leetify

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Performance scores

Aim25

Positioning48

Utility62

0–100 skill scores via Leetify.

Recent form

HOT44–52–4Last 10044%Win rateLWWWWWWLWL

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

Player DNA

Aim2.5

Aggression7.8

Utility6.2

Positioning4.8

Opening Duels4.1

Clutch3.6

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 80% 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

CT openings. Opening success drops from 57% on T to 35% on CT — first contacts on the defending side are being lost.

Reaction time. 653ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 64% 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

Aim2.5

Positioning4.8

Utility6.2

Mechanics3.0

Opening Duels4.1

Win Impact6.1

Composite 3.7/10 (Learning), 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 rating0.00+0.01

first ⅓ avg -0.01 → last ⅓ avg 0.00

Reaction time652ms−26ms

first ⅓ avg 678ms → last ⅓ avg 652ms

Headshot accuracy19.3%−0.8%

first ⅓ avg 20.1% → last ⅓ avg 19.3%

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

0.14Best rating — dust2 13–4

13–0Biggest win — dust2

6Longest win streak

10–9In matches decided by ≤2 rounds

13Overtime games

Map breakdown

mirageBest map · 55% over 11ancientWeakest map · 17% over 12

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	34	17–17	50%	-0.00
nuke	B	21	10–11	48%	-0.01
inferno	D	17	5–12	29%	-0.03
ancient	D	12	2–10	17%	0.00
mirage	A	11	6–5	55%	0.00
anubis	—	2	1–1	50%	0.05
overpass	—	2	2–0	100%	-0.02
cache	—	1	1–0	100%	0.00

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 12). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

470Matches

50%Win rate

0.86Avg K/D

70.2ADR

48%Headshot %

Clutches & streaks

38%1v1 clutch win

20%1v2 clutch win

8Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	145	49%	0.82	13.2
Nuke	80	44%	0.80	12.2
Inferno	75	52%	0.78	12.9
Mirage	66	52%	1.06	13.9
Ancient	54	63%	0.92	13.0
Anubis	23	43%	0.89	13.6
Cache	10	40%	0.71	9.3
Train	9	56%	0.99	13.4

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.

19.7%Headshot accuracy

25.6%Accuracy (enemy spotted)

27.8%Spray accuracy

63.6%Counter-strafing

12.3°Preaim

653msReaction time

57.2%T opening success

35.3%CT opening success

0.62Enemies flashed / flash

6.3%Flash assists

10.07HE damage / grenade

11.61Flashes / 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 12.2925° — above the 12° 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.

17% win rate across 12 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
nuke	6–10	-0.05	14%	28 Jun →
nuke	13–5	0.02	32%	28 Jun →
dust2	13–8	0.08	14%	25 Jun →
mirage	13–11	-0.01	26%	20 Jun →
dust2	13–6	-0.00	23%	17 Jun →
mirage	13–6	0.02	30%	17 Jun →
anubis	13–4	0.09	17%	14 Jun →
ancient	13–16	0.09	16%	14 Jun →
inferno	13–9	0.05	15%	14 Jun →
dust2	10–13	-0.05	26%	13 Jun →
dust2	5–13	0.01	16%	9 Jun →
overpass	13–11	0.02	23%	8 Jun →
dust2	0–13	-0.07	26%	7 Jun →
nuke	9–13	0.09	22%	7 Jun →
dust2	13–10	-0.02	24%	7 Jun →
dust2	13–11	0.07	22%	7 Jun →
overpass	13–11	-0.06	14%	7 Jun →
mirage	13–1	0.08	20%	24 May →
ancient	13–11	0.03	19%	24 May →
dust2	9–13	-0.05	18%	23 May →
mirage	9–13	-0.03	5%	22 May →
dust2	14–16	0.01	25%	21 May →
dust2	10–13	-0.05	16%	21 May →
dust2	13–10	-0.06	19%	20 May →
ancient	11–13	0.04	15%	19 May →
nuke	13–3	-0.00	39%	14 May →
nuke	8–13	-0.08	3%	13 May →
dust2	11–13	0.04	19%	13 May →
nuke	8–13	-0.06	11%	11 May →
nuke	13–6	0.05	32%	10 May →
ancient	5–6	-0.12	0%	10 May →
ancient	4–13	-0.03	18%	10 May →
inferno	13–8	-0.03	18%	10 May →
cache	13–6	0.00	22%	7 May →
ancient	8–13	0.00	20%	6 May →
dust2	9–13	0.01	18%	5 May →
inferno	8–13	0.05	36%	3 May →
ancient	8–13	-0.06	19%	3 May →
nuke	13–7	-0.04	24%	2 May →
inferno	7–13	-0.07	15%	1 May →
dust2	13–9	-0.03	18%	1 May →
mirage	0–7	-0.04	0%	1 May →
inferno	5–13	-0.06	14%	30 Apr →
mirage	13–6	-0.05	35%	30 Apr →
nuke	4–13	-0.08	17%	30 Apr →
dust2	13–9	-0.04	14%	30 Apr →
nuke	16–14	-0.07	20%	26 Apr →
dust2	13–4	-0.00	21%	26 Apr →
nuke	12–16	0.01	19%	26 Apr →
dust2	16–14	0.02	26%	26 Apr →
dust2	8–13	-0.10	24%	25 Apr →
dust2	13–7	-0.06	26%	25 Apr →
nuke	5–13	0.03	29%	25 Apr →
dust2	9–13	0.04	26%	25 Apr →
inferno	14–16	-0.02	19%	23 Apr →
dust2	13–0	0.05	9%	23 Apr →
ancient	14–16	0.02	31%	22 Apr →
mirage	13–1	0.14	15%	22 Apr →
mirage	6–13	-0.02	22%	21 Apr →
inferno	8–13	-0.06	13%	19 Apr →
dust2	4–13	-0.07	25%	19 Apr →
inferno	6–13	-0.01	13%	19 Apr →
dust2	6–13	-0.07	14%	19 Apr →
inferno	13–5	-0.05	14%	18 Apr →
mirage	13–8	-0.07	12%	18 Apr →
dust2	13–10	0.05	24%	18 Apr →
dust2	15–15	0.02	19%	17 Apr →
nuke	13–8	0.03	11%	16 Apr →
nuke	10–13	-0.01	17%	14 Apr →
dust2	7–13	-0.02	16%	14 Apr →
inferno	8–13	-0.00	29%	13 Apr →
ancient	13–10	0.05	18%	13 Apr →
dust2	15–15	0.01	20%	13 Apr →
ancient	6–13	0.04	19%	12 Apr →
nuke	13–6	-0.04	31%	11 Apr →
anubis	8–13	0.01	23%	11 Apr →
inferno	5–13	-0.07	31%	10 Apr →
inferno	15–15	-0.07	27%	10 Apr →
inferno	13–6	-0.00	15%	10 Apr →
dust2	15–15	-0.02	12%	9 Apr →
ancient	5–13	-0.05	27%	8 Apr →
nuke	13–10	0.05	22%	8 Apr →
mirage	6–13	-0.03	17%	7 Apr →
nuke	13–11	-0.02	21%	6 Apr →
mirage	9–13	0.01	15%	5 Apr →
nuke	13–3	-0.01	20%	4 Apr →
dust2	13–2	0.04	20%	4 Apr →
nuke	13–16	-0.01	19%	4 Apr →
dust2	9–13	-0.01	25%	4 Apr →
ancient	11–13	-0.02	30%	3 Apr →
inferno	11–13	-0.04	25%	2 Apr →
inferno	13–11	0.00	16%	1 Apr →
dust2	13–11	0.08	18%	31 Mar →
nuke	2–13	-0.05	16%	29 Mar →
inferno	2–13	0.01	29%	29 Mar →
dust2	13–10	0.03	15%	27 Mar →
dust2	13–8	-0.07	22%	17 Mar →
inferno	8–13	-0.07	13%	15 Mar →
dust2	13–4	0.14	9%	15 Mar →
nuke	14–16	-0.08	21%	15 Mar →