rancho — CS2 Stats

76561197963504494[U:1:3238766]Steam profile ↗✓ No bans

1,915Tracked matches71%Win rate2020Tracked since

CSDB Rating6.4 SolidSupport

CSDB Leaderboard#228939 of 260012 tracked

WingmanMaster Guardian II

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Sep 2026 (65 days ago). Ranks are recorded once per day this page is viewed.

0Faceit ELO · 2,114 → 2,114

+19Tracked matches · now 1,915

+19.0ppWin rate · 51.8% → 70.8%

Rating over time

Premier CS Rating: 23,179 -869 26 Apr – 5 Jun · 10 days played

Faceit ELO: 2,114 +0 30 Aug – 1 Sept · 2 observations

24,292Peak Premier in tracked matches

2,114Highest Faceit ELO seen on CSDB

47Days played since 2026-04-26

Faceit ELO

At peak — 2,114
Next: 2,500 ELO at 2,500 — 386 to go
Reached: Level 10 · Level 9 · Level 8 · Level 7
Level 10 first seen 2026-08-30
Level 9 first seen 2026-08-30

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. 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

Aim71

Positioning54

Utility67

0–100 skill scores via Leetify.

Recent form

HOT52–38–10Last 10052%Win rateWWWWWWWTTW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating · +1.4pp headshot accuracy · −67ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

5–0 · 100% win rate
Avg rating 0.06
Avg headshot accuracy 23%
Avg reaction 492ms

Last 10

8–0–2 · 80% win rate
Avg rating 0.03
Avg headshot accuracy 21%
Avg reaction 500ms

Last 20

14–2–4 · 70% win rate
Avg rating 0.02
Avg headshot accuracy 20%
Avg reaction 534ms

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 (+1.9 against its own average).

Aim7.1

Utility6.7

Positioning5.4

Opening Duels2.7

Clutch4.6

Effective flashes

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 ZywOo 83% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

Reaction time. 555ms 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

Aim7.1

Positioning5.4

Utility6.7

Mechanics6.3

Opening Duels2.2

Win Impact10.0

Composite 6.4/10 (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 rating0.01−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time567ms+22ms

first ⅓ avg 546ms → last ⅓ avg 567ms

Headshot accuracy18.6%−2.4%

first ⅓ avg 21.1% → last ⅓ avg 18.6%

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

0.20Best match rating · 13–7 · dust2, 28 Apr →

54%Best headshot accuracy · 7–2 · dust2, 3 Nov →

328msFastest reaction time · 7–2 · cache, 23 Oct →

13–0Biggest win · cache, 23 Oct →

Across the last 100 tracked matches.

Highlights

7Longest win streak

W7Current streak

7–7In matches decided by ≤2 rounds

4Overtime games

Map breakdown

dust2Best map · 65% over 34infernoWeakest map · 38% over 13

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	40	19–21	48%	0.01
dust2	S	34	22–12	65%	0.03
inferno	C	13	5–8	38%	0.00
nuke	C	5	2–3	40%	0.02
overpass	—	2	1–1	50%	0.02
debris	—	1	0–1	0%	-0.03
fachwerk	—	1	0–1	0%	-0.03
anubis	—	1	1–0	100%	0.03
mirage	—	1	1–0	100%	0.03
vertigo	—	1	1–0	100%	0.01
ancient	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

385Matches

58%Win rate

1.35Avg K/D

86.4ADR

38%Headshot %

Clutches & streaks

43%1v1 clutch win

12%1v2 clutch win

9Longest win streak

Recent Faceit resultsWLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	23	74%	1.41	17.5
Inferno	10	50%	1.12	17.9
Nuke	10	50%	1.23	18.7
Cache	9	67%	1.19	16.0
Ancient	5	40%	1.11	18.8
Mirage	4	25%	1.05	19.8
Anubis	2	50%	0.82	14.0
Overpass	2	50%	1.08	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.

18.1%Headshot accuracy

37.6%Accuracy (enemy spotted)

40.4%Spray accuracy

78.5%Counter-strafing

12.4°Preaim

555msReaction time

40.0%T opening success

37.3%CT opening success

0.72Enemies flashed / flash

10.2%Flash assists

10.59HE damage / grenade

12.52Flashes / 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 12.4201° — 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.

38% win rate across 13 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
nuke	13–6	-0.01	21%	3 Nov →
dust2	7–2	0.18	54%	3 Nov →
inferno	13–8	0.08	13%	3 Nov →
cache	13–3	0.03	14%	3 Nov →
dust2	13–10	0.05	11%	2 Nov →
dust2	8–0	0.05	25%	28 Oct →
inferno	13–6	-0.03	29%	28 Oct →
cache	12–12	-0.06	16%	27 Oct →
cache	15–15	-0.02	17%	25 Oct →
cache	13–1	0.06	9%	23 Oct →
dust2	6–13	-0.01	24%	23 Oct →
cache	13–0	-0.02	7%	23 Oct →
cache	7–2	-0.01	29%	23 Oct →
dust2	13–11	-0.01	21%	21 Oct →
cache	12–12	-0.01	23%	21 Oct →
dust2	13–10	0.05	14%	20 Oct →
dust2	13–6	0.04	18%	8 Oct →
cache	12–12	0.02	21%	24 Sept →
cache	13–3	0.00	16%	17 Sept →
cache	4–13	0.01	23%	28 Aug →
cache	9–13	-0.04	12%	27 Aug →
nuke	9–7	0.06	13%	1 Aug →
debris	6–9	-0.03	27%	1 Aug →
inferno	3–9	-0.13	9%	1 Aug →
cache	3–13	-0.00	10%	23 Jul →
cache	13–10	0.04	21%	22 Jul →
dust2	3–13	-0.08	21%	14 Jul →
inferno	12–12	0.06	17%	11 Jul →
dust2	13–7	0.03	14%	10 Jul →
fachwerk	3–13	-0.03	19%	9 Jul →
dust2	15–15	-0.02	13%	9 Jul →
cache	13–2	0.01	16%	9 Jul →
dust2	14–16	0.04	21%	8 Jul →
inferno	9–13	-0.01	35%	2 Jul →
cache	7–13	-0.04	31%	1 Jul →
dust2	13–6	0.00	20%	21 Jun →
dust2	1–2	-0.06	17%	21 Jun →
dust2	13–7	0.06	36%	20 Jun →
cache	13–7	0.01	27%	8 Jun →
dust2	13–6	0.00	16%	5 Jun →
dust2	13–7	0.03	18%	5 Jun →
cache	13–8	0.06	24%	5 Jun →
inferno	13–11	0.10	18%	5 Jun →
dust2	11–13	-0.02	21%	4 Jun →
nuke	8–13	-0.00	13%	4 Jun →
cache	12–12	-0.01	22%	2 Jun →
dust2	13–2	0.06	27%	31 May →
anubis	13–7	0.03	19%	31 May →
inferno	5–13	0.00	27%	31 May →
cache	3–13	-0.10	14%	31 May →
cache	13–6	0.06	17%	31 May →
dust2	13–6	0.08	12%	31 May →
dust2	8–13	0.09	20%	30 May →
inferno	13–6	-0.02	7%	30 May →
cache	13–6	0.03	17%	30 May →
overpass	13–10	0.05	14%	28 May →
dust2	13–8	0.01	15%	27 May →
cache	13–1	0.06	26%	27 May →
mirage	13–9	0.03	22%	22 May →
dust2	13–8	0.04	33%	22 May →
cache	8–13	0.01	18%	22 May →
cache	8–13	-0.04	22%	22 May →
cache	13–10	0.06	12%	20 May →
inferno	8–13	0.03	13%	19 May →
dust2	5–13	-0.01	38%	19 May →
overpass	7–9	-0.01	16%	19 May →
dust2	13–4	0.03	27%	16 May →
cache	11–13	-0.02	29%	16 May →
dust2	13–2	0.05	14%	14 May →
cache	7–13	0.03	32%	14 May →
cache	12–12	0.02	27%	14 May →
cache	13–4	0.00	20%	14 May →
inferno	5–13	0.02	14%	14 May →
dust2	13–6	0.11	14%	14 May →
cache	9–13	0.02	24%	14 May →
vertigo	13–4	0.01	22%	12 May →
inferno	13–11	-0.01	11%	9 May →
inferno	9–13	-0.05	16%	9 May →
nuke	9–13	0.02	25%	9 May →
dust2	12–12	0.00	23%	8 May →
cache	7–13	-0.01	23%	8 May →
cache	13–11	0.01	10%	7 May →
dust2	8–13	-0.08	22%	7 May →
dust2	11–13	0.01	18%	7 May →
cache	13–2	0.04	20%	5 May →
cache	13–2	0.11	27%	5 May →
cache	4–4	-0.05	20%	5 May →
cache	10–13	0.01	27%	29 Apr →
cache	12–12	0.08	28%	29 Apr →
cache	11–13	-0.01	20%	29 Apr →
cache	10–13	-0.05	17%	29 Apr →
cache	13–9	0.04	27%	29 Apr →
dust2	13–7	0.20	20%	28 Apr →
ancient	9–13	0.01	16%	28 Apr →
nuke	10–13	0.03	20%	28 Apr →
dust2	0–13	-0.03	45%	27 Apr →
dust2	13–10	-0.02	17%	27 Apr →
inferno	8–13	-0.02	9%	27 Apr →
dust2	13–6	0.18	9%	26 Apr →
dust2	16–14	0.05	29%	26 Apr →