Margaret Thatcher — CS2 Stats

US76561198087159693[U:1:126893965]Steam profile ↗✓ No bans

610Tracked matches63%Win rate2020Tracked since

3,969Hours in CS1Hrs last 2 wks

CSDB Rating8.0 StrongAggressive Rifler

Ladder ranks via Leetify

Performance scores

Aim95

Positioning67

Utility62

0–100 skill scores via Leetify.

Recent form

STEADY57–34–9Last 10057%Win rateLLLWLWWWWW

Last 10 vs previous 10: +10pp win rate · -0.00 avg rating

Player DNA

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

Aim9.5

Aggression10.0

Utility6.2

Positioning6.7

Opening Duels5.2

Clutch4.0

Sharp aimerExcellent counter-strafingEffective flashes

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 sh1ro 98% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

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

Aim. Aim score of 95 — the mechanical foundation is a clear strength.

Counter-strafing. 92% of shots taken properly stopped — movement discipline most players never reach.

Flashes. 0.77 enemies blinded per flash — utility that consistently lands.

Areas to improve

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

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

Aim9.5

Positioning6.7

Utility6.2

Mechanics9.3

Opening Duels5.2

Win Impact9.4

Composite 8.0/10 (Strong), 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 rating0.03−0.01

first ⅓ avg 0.05 → last ⅓ avg 0.03

Reaction time546ms−55ms

first ⅓ avg 601ms → last ⅓ avg 546ms

Headshot accuracy26.1%+3.0%

first ⅓ avg 23.1% → last ⅓ avg 26.1%

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

0.18Best rating — nuke 13–8

13–2Biggest win — cache

8Longest win streak

L3Current streak

8–11In matches decided by ≤2 rounds

5Overtime games

Map breakdown

nukeBest map · 91% over 11infernoWeakest map · 42% over 12

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	26	13–13	50%	0.03
mirage	B	19	9–10	47%	0.03
dust2	S	16	11–5	69%	0.04
inferno	C	12	5–7	42%	0.03
nuke	S	11	10–1	91%	0.09
overpass	B	6	3–3	50%	0.04
ancient	—	4	4–0	100%	0.05
anubis	—	3	1–2	33%	-0.02
office	—	2	0–2	0%	0.07
train	—	1	1–0	100%	0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

120,071Lifetime kills

0.89K/D

2,361Matches

49.9%Match win rate · Top 25% of tracked players

40.3%Headshot %

21.6%Shot accuracy · Top 5% of tracked players

5,358MVPs

2,554Hours (in match)

3,864Bombs planted

1,273Bombs defused

Most-used weapons

AK-4742,270

AWP30,491

M4A4 / M4A1-S15,026

P2000 / USP-S8,245

Desert Eagle3,794

Glock-183,440

P2503,266

Knife1,746

Tec-91,683

Five-SeveN1,460

Lifetime map wins

6,823inferno

5,380dust2

5,205nuke

2,581train

1,400cbble

856vertigo

300office

146italy

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

Faceit stats

Combat

251Matches

56%Win rate

1.20Avg K/D

89.4ADR

38%Headshot %

Clutches & streaks

40%1v1 clutch win

19%1v2 clutch win

8Longest win streak

Recent Faceit resultsWLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	12	58%	1.34	20.3
Anubis	8	38%	1.17	18.1
Dust2	8	38%	1.25	17.3
Ancient	6	67%	1.51	21.2
Cache	5	60%	1.93	20.2
Nuke	5	60%	1.34	19.4
Vertigo	2	0%	0.54	9.5
Inferno	2	50%	0.96	15.0

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.

27.4%Headshot accuracy

38.7%Accuracy (enemy spotted)

46.2%Spray accuracy

92.0%Counter-strafing

8.0°Preaim

545msReaction time

50.6%T opening success

51.2%CT opening success

0.77Enemies flashed / flash

4.5%Flash assists

11.01HE damage / grenade

9.44Flashes / match

Recommended for you

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.

42% win rate across 12 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	7–13	-0.06	29%	20 Aug →
mirage	8–13	-0.05	27%	20 Aug →
cache	3–13	-0.07	20%	5 Aug →
inferno	16–13	0.06	33%	29 Jul →
mirage	10–13	0.06	28%	29 Jul →
mirage	13–8	0.12	22%	28 Jul →
nuke	13–10	0.03	41%	28 Jul →
dust2	13–3	0.12	11%	28 Jul →
ancient	13–8	0.05	21%	26 Jul →
nuke	13–7	0.06	19%	23 Jul →
cache	13–5	0.08	11%	23 Jul →
mirage	7–13	-0.05	21%	21 Jul →
cache	11–13	0.03	37%	15 Jul →
ancient	13–8	0.06	14%	13 Jul →
cache	13–6	0.10	33%	10 Jul →
cache	11–13	0.04	54%	10 Jul →
inferno	13–3	0.08	29%	10 Jul →
cache	13–4	0.02	31%	10 Jul →
mirage	11–13	0.03	27%	10 Jul →
cache	4–13	-0.06	26%	9 Jul →
mirage	13–6	0.10	24%	9 Jul →
ancient	13–5	0.02	20%	9 Jul →
cache	13–6	0.02	19%	9 Jul →
dust2	13–11	0.01	32%	8 Jul →
cache	13–4	-0.00	29%	8 Jul →
anubis	6–13	0.00	18%	5 Jul →
mirage	11–13	0.00	20%	5 Jul →
dust2	16–12	0.08	29%	2 Jul →
dust2	13–11	0.04	42%	25 Jun →
nuke	13–8	0.18	38%	24 Jun →
nuke	8–13	0.00	12%	15 Jun →
mirage	11–13	-0.04	12%	12 Jun →
cache	13–9	0.02	35%	10 Jun →
cache	13–7	0.01	30%	10 Jun →
nuke	13–6	0.06	19%	5 Jun →
ancient	13–11	0.05	34%	5 Jun →
dust2	13–5	0.07	39%	5 Jun →
cache	13–6	0.15	26%	29 May →
mirage	13–6	0.07	21%	27 May →
mirage	9–13	-0.06	18%	27 May →
cache	13–2	0.07	21%	27 May →
cache	11–13	-0.01	29%	27 May →
cache	13–11	0.04	27%	22 May →
cache	4–13	0.01	20%	22 May →
cache	11–13	0.02	29%	22 May →
cache	12–12	0.05	28%	20 May →
cache	12–12	0.09	27%	3 May →
cache	13–5	0.13	19%	3 May →
cache	13–10	0.06	22%	2 May →
cache	2–9	0.02	44%	2 May →
cache	12–12	-0.03	22%	2 May →
cache	12–12	0.10	22%	2 May →
cache	12–12	0.02	15%	1 May →
cache	13–11	-0.01	38%	1 May →
inferno	13–10	0.07	18%	28 Apr →
dust2	13–9	0.02	24%	28 Apr →
mirage	13–7	0.05	27%	27 Apr →
inferno	13–4	0.01	21%	27 Apr →
anubis	13–9	0.01	23%	22 Apr →
mirage	13–8	0.02	25%	22 Apr →
dust2	13–8	0.01	10%	22 Apr →
dust2	8–13	-0.01	18%	22 Apr →
dust2	13–3	-0.02	33%	21 Apr →
inferno	4–7	0.03	26%	20 Apr →
mirage	13–2	0.07	22%	19 Apr →
mirage	13–11	0.08	29%	19 Apr →
inferno	13–8	0.11	16%	19 Apr →
inferno	1–13	-0.02	35%	19 Apr →
dust2	13–6	0.05	18%	18 Apr →
dust2	13–6	0.11	20%	18 Apr →
overpass	11–13	0.03	32%	18 Apr →
nuke	13–9	0.10	29%	18 Apr →
overpass	13–6	0.02	20%	18 Apr →
dust2	14–16	0.05	25%	17 Apr →
mirage	13–9	0.05	24%	17 Apr →
mirage	8–13	0.02	12%	11 Apr →
train	13–4	0.06	28%	10 Apr →
mirage	15–15	0.01	20%	7 Apr →
inferno	15–15	-0.02	24%	7 Apr →
dust2	11–13	0.05	26%	6 Apr →
overpass	13–6	-0.02	35%	6 Apr →
inferno	1–3	0.04	50%	1 Apr →
nuke	9–1	0.12	25%	29 Mar →
inferno	2–13	-0.09	0%	29 Mar →
overpass	3–13	0.04	23%	29 Mar →
mirage	13–11	0.12	24%	25 Mar →
nuke	13–3	0.15	32%	25 Mar →
nuke	13–9	0.09	17%	14 Mar →
nuke	13–10	0.06	9%	14 Mar →
inferno	12–12	0.10	26%	14 Mar →
overpass	13–2	0.10	33%	14 Mar →
dust2	13–2	0.17	24%	14 Mar →
office	9–13	0.07	25%	14 Mar →
inferno	9–13	-0.02	15%	13 Mar →
mirage	9–13	-0.01	15%	8 Mar →
overpass	12–12	0.06	20%	8 Mar →
anubis	0–13	-0.07	0%	7 Mar →
nuke	13–11	0.09	34%	7 Mar →
dust2	2–13	-0.00	23%	7 Mar →
office	10–13	0.08	19%	24 Jan →