Madam 🌹 — CS2 Stats

LT76561197984057399[U:1:23791671]Steam profile ↗✓ No bans

5,552Tracked matches63%Win rate2020Tracked since

CSDB Rating6.1 SolidSupport

CSDB Leaderboard#210065 of 257783 tracked

FaceitLevel 10 · 3,145 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 19 Oct 2026 (8 days ago). Ranks are recorded once per day this page is viewed.

0Faceit ELO · 3,145 → 3,145

+25Tracked matches · now 5,552

+3.3ppWin rate · 60.0% → 63.3%

Rating over time

Faceit ELO: 3,145 +0 1 Sept – 19 Oct · 4 observations

3,145Highest Faceit ELO seen on CSDB

70Days played since 2025-09-17

Faceit ELO

At peak — 3,145
0 over 30 days · steady
Next: 3,500 ELO at 3,500 — 355 to go
Reached: 3,000 ELO · 2,500 ELO · Level 10 · Level 9
3,000 ELO first seen 2026-09-01
2,500 ELO first seen 2026-09-01

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

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Performance scores

Aim76

Positioning46

Utility54

0–100 skill scores via Leetify.

Recent form

STEADY57–43Last 10057%Win rateWLWWWLLLWL

Last 10 vs previous 10: −30pp win rate · +0.03 avg rating · +0.7pp headshot accuracy · +20ms reaction

Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

4–1 · 80% win rate
Avg rating 0.03
Avg headshot accuracy 21%
Avg reaction 544ms

Last 10

5–5 · 50% win rate
Avg rating 0.01
Avg headshot accuracy 18%
Avg reaction 526ms

Last 20

13–7 · 65% win rate
Avg rating -0.00
Avg headshot accuracy 18%
Avg reaction 516ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.4 against its own average).

Aim7.6

Utility5.4

Positioning4.6

Opening Duels2.3

Clutch3.6

Strong 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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like NiKo 93% playstyle similarity

Most alike: utility contribution, aim profile.

Where you differ: lower positioning profile; lower opening-duel success.

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

Positioning. Positioning trails aim by 30 points — deaths here waste a strong aim profile.

T-side openings. Opening success drops from 49% on CT to 24% on T — the same duels are being taken with worse setups on the attacking side.

Counter-strafing. Only 69% 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

Aim7.6

Positioning4.6

Utility5.4

Mechanics4.3

Opening Duels2.4

Win Impact9.4

Composite 6.1/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 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 time508ms−6ms

first ⅓ avg 514ms → last ⅓ avg 508ms

Headshot accuracy16.1%+1.7%

first ⅓ avg 14.4% → last ⅓ avg 16.1%

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.

Personal bests

0.08Best match rating · 13–5 · nuke, 5 Jul →

32%Best headshot accuracy · 5–13 · inferno, 1 Oct →

320msFastest reaction time · 13–8 · anubis, 19 Aug →

13–2Biggest win · anubis, 21 Jul →

Across the last 100 tracked matches.

Highlights

9Longest win streak

16–7In matches decided by ≤2 rounds

15Overtime games

Map breakdown

overpassBest map · 86% over 7mirageWeakest map · 41% over 17

Map	Grade	Played	Record	Win rate	Avg rating
ancient	C	23	10–13	43%	0.00
inferno	S	18	12–6	67%	0.01
mirage	C	17	7–10	41%	-0.01
dust2	B	13	7–6	54%	-0.02
anubis	S	12	8–4	67%	0.01
nuke	S	10	7–3	70%	-0.00
overpass	S	7	6–1	86%	-0.01

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (41% over 17). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

8,658Matches

51%Win rate

1.08Avg K/D

74.0ADR

39%Headshot %

Clutches & streaks

38%1v1 clutch win

21%1v2 clutch win

13Longest win streak

Recent Faceit resultsLWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	1030	51%	1.02	14.8
Anubis	892	53%	1.04	14.8
Mirage	624	48%	0.97	14.0
Dust2	592	50%	0.96	13.8
Inferno	364	49%	1.04	14.8
Nuke	320	49%	1.04	14.7
Vertigo	227	49%	1.00	14.8
Overpass	160	54%	1.07	15.4

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.

16.1%Headshot accuracy

38.4%Accuracy (enemy spotted)

43.6%Spray accuracy

69.4%Counter-strafing

9.8°Preaim

509msReaction time

24.2%T opening success

49.3%CT opening success

0.63Enemies flashed / flash

6.5%Flash assists

6.10HE damage / grenade

8.94Flashes / 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 24.164% — below the 40% mark we flag

Spend your practice time on Mirage

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 17 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

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