Edu — CS2 Stats

76561198084509917[U:1:124244189]Steam profile ↗✓ No bans

947Tracked matches57%Win rate2020Tracked since

1,662Hours in CS

CSDB Rating6.0 SolidAggressive Rifler

WingmanSupreme Master First Class

Ladder ranks via Leetify

Performance scores

Aim70

Positioning58

Utility30

0–100 skill scores via Leetify.

Recent form

STEADY54–39–7Last 10054%Win rateLWWTWLLLWT

Last 10 vs previous 10: -10pp win rate · -0.08 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.0

Aggression8.0

Utility3.0

Positioning5.8

Opening Duels3.7

Clutch5.4

Strong CT-side openerLimited utility dependence

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 ropz 86% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 55% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 573ms 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

Aim7.0

Positioning5.8

Utility3.0

Mechanics7.6

Opening Duels3.7

Win Impact7.4

Composite 6.0/10 (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 rating0.01−0.00

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time601ms−2ms

first ⅓ avg 603ms → last ⅓ avg 601ms

Headshot accuracy16.4%−1.7%

first ⅓ avg 18.1% → last ⅓ avg 16.4%

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

0.37Best rating — inferno 9–0

13–2Biggest win — anubis

8Longest win streak

6–9In matches decided by ≤2 rounds

9Overtime games

Map breakdown

infernoBest map · 71% over 14nukeWeakest map · 27% over 11

Map	Grade	Played	Record	Win rate	Avg rating
ancient	S	21	14–7	67%	0.01
mirage	B	20	9–11	45%	-0.00
inferno	S	14	10–4	71%	0.03
nuke	D	11	3–8	27%	-0.03
anubis	S	10	7–3	70%	0.03
vertigo	A	7	4–3	57%	0.04
dust2	C	5	2–3	40%	-0.02
train	C	5	2–3	40%	-0.02
overpass	—	3	1–2	33%	-0.02
aim_all_pistols	—	1	0–1	0%	-0.04
eldorado	—	1	0–1	0%	-0.03
debris	—	1	1–0	100%	0.12
cache	—	1	1–0	100%	-0.03

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

89,820Lifetime kills

1.23K/D · Top 25% of tracked players

4,574Matches

49.7%Match win rate · Top 25% of tracked players

45.3%Headshot % · Top 50% of tracked players

13.9%Shot accuracy · Top 50% of tracked players

12,395MVPs

1,662Hours (in match)

3,940Bombs planted

1,644Bombs defused

Most-used weapons

AK-4726,565

M4A4 / M4A1-S11,687

AWP11,078

P2000 / USP-S7,845

Desert Eagle5,907

Glock-183,289

P2502,465

Galil AR1,830

SSG 081,756

Tec-91,684

Lifetime map wins

5,282inferno

4,774dust2

3,307train

2,356vertigo

2,355nuke

711cbble

100dust

97office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

309Matches

58%Win rate

1.20Avg K/D

75.5ADR

41%Headshot %

Clutches & streaks

47%1v1 clutch win

20%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	70	53%	1.08	15.7
Ancient	52	62%	1.13	16.3
Anubis	38	61%	1.34	17.9
Vertigo	36	67%	1.45	16.0
Dust2	10	30%	1.01	15.0
Inferno	8	50%	0.96	12.9
Nuke	6	67%	1.08	13.5
Train	3	33%	1.02	18.7

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.

15.8%Headshot accuracy

33.8%Accuracy (enemy spotted)

33.5%Spray accuracy

84.3%Counter-strafing

9.0°Preaim

573msReaction time

34.9%T opening success

54.5%CT opening success

0.42Enemies flashed / flash

1.7%Flash assists

11.28HE damage / grenade

3.35Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4154 — below the 0.5 mark we flag
Grenade Lineups →
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 34.8728% — below the 40% mark we flag

Spend your practice time on Nuke

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

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	11–13	-0.00	18%	9 Aug →
mirage	13–8	0.01	6%	9 Aug →
nuke	9–6	0.07	8%	5 Aug →
nuke	8–8	-0.07	15%	5 Aug →
nuke	9–4	-0.04	16%	5 Aug →
nuke	3–9	-0.13	8%	5 Aug →
aim_all_pistols	13–16	-0.04	22%	4 Aug →
overpass	6–9	-0.19	19%	3 Aug →
overpass	9–1	0.12	10%	3 Aug →
overpass	8–8	-0.01	9%	3 Aug →
vertigo	8–8	-0.01	17%	3 Aug →
nuke	8–8	0.05	16%	3 Aug →
vertigo	5–9	-0.16	12%	2 Aug →
vertigo	9–2	0.10	33%	2 Aug →
vertigo	9–0	0.29	21%	2 Aug →
inferno	9–6	-0.08	13%	2 Aug →
inferno	9–0	0.37	32%	2 Aug →
inferno	9–1	0.06	10%	2 Aug →
vertigo	7–9	-0.06	9%	2 Aug →
eldorado	6–9	-0.03	15%	2 Aug →
nuke	6–9	-0.08	17%	2 Aug →
vertigo	9–2	0.15	29%	2 Aug →
inferno	9–7	-0.02	11%	2 Aug →
nuke	3–9	-0.07	25%	2 Aug →
debris	9–4	0.12	20%	2 Aug →
inferno	5–9	-0.11	16%	2 Aug →
cache	13–10	-0.03	12%	28 Jul →
dust2	13–6	-0.01	26%	8 Apr →
anubis	13–8	0.07	16%	30 Mar →
mirage	13–5	0.01	15%	28 Mar →
ancient	13–9	0.06	23%	28 Mar →
mirage	11–13	-0.04	16%	28 Mar →
ancient	6–13	-0.07	6%	28 Mar →
inferno	13–10	0.04	10%	28 Mar →
anubis	6–0	0.11	7%	28 Mar →
dust2	15–15	-0.00	5%	27 Mar →
ancient	13–8	-0.01	11%	25 Mar →
dust2	14–16	-0.05	14%	13 Mar →
mirage	15–15	-0.01	21%	12 Mar →
mirage	13–10	-0.07	14%	12 Mar →
inferno	13–11	-0.03	31%	11 Mar →
inferno	13–5	0.05	14%	11 Mar →
mirage	11–13	-0.01	18%	13 Feb →
mirage	5–13	-0.04	20%	13 Feb →
ancient	13–7	-0.02	15%	13 Feb →
mirage	8–13	-0.00	16%	6 Nov →
nuke	4–9	0.03	13%	15 Jun →
dust2	16–14	-0.00	14%	13 Jun →
nuke	10–13	-0.03	19%	13 Jun →
mirage	9–13	0.01	14%	11 Jun →
ancient	6–13	-0.01	26%	6 Jun →
ancient	13–3	-0.03	18%	6 Jun →
train	11–13	-0.05	15%	24 May →
ancient	13–5	-0.01	17%	24 May →
ancient	6–2	-0.04	11%	24 May →
dust2	8–13	-0.04	24%	23 May →
train	16–12	0.01	20%	13 May →
ancient	10–13	0.03	15%	11 May →
inferno	13–11	-0.02	17%	10 May →
anubis	11–13	-0.06	32%	4 May →
inferno	13–5	0.11	16%	3 May →
mirage	13–8	-0.03	11%	3 May →
ancient	13–9	-0.01	14%	3 May →
mirage	8–13	0.02	14%	2 May →
inferno	2–13	-0.02	12%	12 Apr →
inferno	8–8	0.05	12%	1 Mar →
inferno	13–11	0.06	26%	25 Feb →
mirage	13–8	-0.02	7%	24 Feb →
anubis	13–2	0.03	16%	23 Feb →
ancient	10–13	0.04	16%	6 Feb →
train	7–13	-0.02	27%	19 Jan →
train	6–13	-0.01	32%	19 Jan →
ancient	13–10	0.02	10%	17 Jan →
train	13–8	-0.03	20%	16 Jan →
nuke	9–13	-0.02	29%	12 Jan →
mirage	6–13	0.01	12%	11 Jan →
ancient	13–3	0.01	21%	11 Jan →
vertigo	13–2	-0.00	17%	11 Jan →
ancient	13–11	0.05	16%	11 Jan →
anubis	13–10	0.04	17%	11 Jan →
mirage	13–10	0.01	11%	11 Jan →
mirage	13–3	0.03	21%	11 Jan →
ancient	13–2	0.05	23%	11 Jan →
mirage	13–9	0.09	20%	10 Jan →
ancient	11–13	0.03	22%	10 Jan →
anubis	10–13	0.09	10%	9 Jan →
nuke	13–9	-0.04	13%	9 Jan →
mirage	2–13	-0.03	17%	5 Jan →
mirage	13–10	0.01	24%	5 Jan →
anubis	13–5	0.02	8%	4 Jan →
mirage	12–16	0.01	19%	15 Dec →
ancient	13–8	0.05	11%	15 Dec →
inferno	9–13	-0.02	20%	15 Dec →
anubis	4–13	-0.03	28%	15 Dec →
ancient	13–9	0.05	26%	15 Dec →
mirage	11–13	-0.07	20%	6 Dec →
ancient	19–16	0.01	17%	4 Dec →
ancient	13–16	-0.01	16%	1 Dec →
anubis	13–4	-0.00	10%	1 Dec →
anubis	13–8	0.01	21%	1 Dec →