MoedieHoe — CS2 Stats

GB76561198375690268[U:1:415424540]Steam profile ↗✓ No bans

1,650Tracked matches39%Win rate2020Tracked since

CSDB Rating4.2 Developing

CSDB Leaderboard#42695 of 46446 tracked

WingmanDistinguished Master Guardian

Ladder ranks via Leetify

Rating over time

1,882Peak Faceit ELO on CSDB

1Days observed since 2026-08-30

Faceit ELO

At peak — 1,882
Next: Level 10 at 2,001 — 119 to go
Reached: Level 9 · Level 8 · Level 7 · Level 6
Level 9 first seen 2026-08-30
Level 8 first seen 2026-08-30

CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.

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Performance scores

Aim57

Positioning48

Utility44

0–100 skill scores via Leetify.

Recent form

STEADY46–50–4Last 10046%Win rateWWLLWWTLLW

Last 10 vs previous 10: +40pp win rate · +0.01 avg rating

Player DNA

Aim5.7

Aggression5.6

Utility4.4

Positioning4.8

Opening Duels2.6

Clutch3.0

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 NiKo 85% playstyle similarity

Most alike: opening-fight frequency, 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

Reaction time. 620ms 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

Aim5.7

Positioning4.8

Utility4.4

Mechanics4.6

Opening Duels2.6

Win Impact1.4

Composite 4.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.02

first ⅓ avg -0.01 → last ⅓ avg 0.01

Reaction time627ms−28ms

first ⅓ avg 655ms → last ⅓ avg 627ms

Headshot accuracy17.7%+1.4%

first ⅓ avg 16.3% → last ⅓ avg 17.7%

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

0.11Best rating — inferno 13–3

13–1Biggest win — anubis

8Longest win streak

W2Current streak

9–11In matches decided by ≤2 rounds

13Overtime games

Map breakdown

dust2Best map · 64% over 11nukeWeakest map · 29% over 17

Map	Grade	Played	Record	Win rate	Avg rating
nuke	D	17	5–12	29%	-0.01
inferno	D	16	5–11	31%	0.01
mirage	A	14	8–6	57%	0.02
ancient	B	13	7–6	54%	0.01
anubis	B	13	6–7	46%	-0.01
dust2	A	11	7–4	64%	0.01
overpass	—	4	2–2	50%	-0.03
train	—	4	3–1	75%	-0.02
cache	—	3	0–3	0%	-0.02
vertigo	—	3	1–2	33%	0.00
office	—	1	1–0	100%	0.00
agency	—	1	1–0	100%	0.02

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (29% over 17). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,360Matches

49%Win rate

1.02Avg K/D

81.5ADR

44%Headshot %

Clutches & streaks

35%1v1 clutch win

21%1v2 clutch win

12Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	243	50%	1.03	16.2
Anubis	219	51%	1.00	15.7
Mirage	198	38%	0.94	14.5
Ancient	194	52%	1.01	16.2
Dust2	138	43%	0.95	14.7
Nuke	134	51%	1.03	16.8
Vertigo	119	61%	1.10	16.3
Train	54	65%	1.22	17.0

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.

17.4%Headshot accuracy

36.1%Accuracy (enemy spotted)

40.3%Spray accuracy

70.5%Counter-strafing

12.0°Preaim

620msReaction time

39.1%T opening success

41.8%CT opening success

0.63Enemies flashed / flash

11.8%Flash assists

8.73HE damage / grenade

4.12Flashes / 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 39.1263% — 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.

29% win rate across 17 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	13–9	0.07	9%	23 Aug →
anubis	13–11	0.03	27%	18 Aug →
mirage	4–13	-0.02	11%	18 Aug →
cache	2–13	-0.08	14%	17 Aug →
dust2	13–10	0.02	13%	17 Aug →
nuke	13–3	0.00	11%	16 Aug →
inferno	15–15	0.00	18%	13 Aug →
ancient	8–13	0.01	17%	12 Aug →
nuke	7–13	0.00	23%	31 Jul →
ancient	13–9	0.07	19%	30 Jul →
cache	8–13	-0.03	23%	29 Jul →
inferno	8–13	0.02	19%	29 Jul →
nuke	14–16	-0.03	22%	29 Jul →
dust2	13–11	0.06	13%	29 Jul →
anubis	7–13	-0.04	26%	29 Jul →
anubis	11–13	0.02	22%	24 Jul →
ancient	6–13	-0.01	19%	12 Jul →
vertigo	8–13	-0.03	18%	10 Jul →
cache	14–16	0.05	14%	9 Jul →
nuke	4–13	0.01	22%	9 Jul →
dust2	13–9	-0.05	27%	19 Jun →
ancient	13–9	0.04	18%	14 Jun →
nuke	13–6	0.03	23%	12 Jun →
mirage	9–13	0.02	10%	12 Jun →
inferno	13–3	0.11	18%	9 Jun →
ancient	8–13	-0.04	18%	8 Jun →
anubis	15–15	0.00	15%	8 Jun →
ancient	13–10	0.05	15%	8 Jun →
overpass	11–13	-0.05	10%	4 Jun →
inferno	14–16	0.00	9%	4 Jun →
ancient	9–13	0.02	20%	1 Jun →
nuke	11–13	-0.01	21%	1 Jun →
dust2	3–13	-0.07	20%	1 Jun →
nuke	3–13	-0.02	14%	31 May →
nuke	13–8	0.09	15%	31 May →
inferno	9–13	-0.06	18%	31 May →
inferno	16–14	0.01	26%	31 May →
ancient	13–6	0.00	11%	8 May →
anubis	13–7	0.05	23%	7 May →
nuke	4–13	-0.06	10%	21 Apr →
nuke	11–13	-0.01	18%	17 Apr →
inferno	13–9	-0.05	18%	17 Apr →
dust2	15–15	0.04	17%	13 Apr →
anubis	13–5	-0.01	29%	28 Mar →
inferno	13–10	0.05	21%	28 Mar →
dust2	13–6	0.03	20%	26 Mar →
nuke	8–13	-0.01	21%	25 Mar →
inferno	8–13	0.02	15%	24 Mar →
mirage	13–11	0.02	14%	22 Mar →
inferno	10–13	-0.01	12%	22 Mar →
mirage	9–13	0.07	19%	22 Mar →
mirage	13–11	-0.03	18%	21 Mar →
mirage	11–13	0.03	20%	21 Mar →
mirage	13–9	0.07	11%	21 Mar →
inferno	4–13	-0.04	26%	21 Mar →
anubis	13–8	-0.02	22%	19 Mar →
anubis	5–13	-0.08	22%	24 Feb →
dust2	11–13	0.03	16%	17 Feb →
anubis	13–1	0.02	8%	26 Jan →
vertigo	12–12	0.04	15%	19 Jan →
mirage	13–10	0.04	20%	18 Jan →
train	8–13	-0.08	24%	13 Jan →
mirage	13–5	0.08	19%	11 Jan →
vertigo	13–10	0.01	12%	13 Dec →
inferno	5–13	0.04	13%	21 Nov →
nuke	5–13	-0.10	14%	11 Oct →
dust2	10–13	-0.02	16%	11 Oct →
overpass	13–9	-0.01	9%	9 Oct →
ancient	6–13	-0.02	15%	1 Oct →
office	13–10	0.00	27%	30 Sept →
dust2	13–2	0.07	18%	17 Sept →
train	19–17	-0.02	16%	17 Sept →
train	13–7	0.03	30%	17 Sept →
dust2	13–11	-0.05	19%	9 Sept →
train	16–14	-0.00	31%	6 Sept →
mirage	13–5	0.07	10%	6 Sept →
overpass	13–4	-0.05	14%	26 Aug →
inferno	7–9	0.01	10%	20 Aug →
overpass	8–13	0.01	14%	10 Aug →
dust2	13–4	0.07	30%	9 Aug →
mirage	16–12	-0.02	13%	8 Aug →
ancient	19–15	-0.01	13%	30 Jul →
inferno	8–13	0.03	24%	29 Jul →
inferno	6–13	-0.00	11%	21 Jul →
nuke	12–5	0.01	21%	8 Jul →
ancient	4–13	-0.04	12%	6 Jul →
anubis	2–13	-0.10	5%	4 Jul →
mirage	7–13	0.01	14%	2 Jul →
nuke	16–14	-0.03	7%	1 Jul →
nuke	8–13	-0.03	19%	27 Jun →
inferno	13–10	-0.05	13%	19 Jun →
nuke	1–13	-0.07	13%	19 Jun →
mirage	13–16	-0.06	9%	17 Jun →
anubis	13–3	-0.02	13%	15 Jun →
anubis	9–13	-0.04	16%	12 Jun →
mirage	13–3	-0.02	22%	12 Jun →
ancient	13–3	-0.02	36%	11 Jun →
agency	13–5	0.02	11%	11 Jun →
nuke	10–13	-0.01	13%	9 Jun →
anubis	11–13	0.02	14%	5 Jun →