Gerhardt GUMMIAND — CS2 Stats

KP76561198042935173[U:1:82669445]Steam profile ↗✓ No bans

1,868Tracked matches35%Win rate2020Tracked since

CSDB Rating5.4 DevelopingAggressive Rifler

Premier CS Rating19,337Purple band · top ~11.1% of ranked players (population est.)

CSDB Leaderboard#24499 of 58442 tracked

WingmanMaster Guardian Elite

Ladder ranks via Leetify

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Performance scores

Aim73

Positioning61

Utility40

0–100 skill scores via Leetify.

Recent form

STEADY35–60–5Last 10035%Win rateWWTWTTLWLW

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating

Player DNA

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

Aim7.3

Aggression7.1

Utility4.0

Positioning6.1

Opening Duels3.8

Clutch4.8

Limited 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 91% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

Where you differ: 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.

Reaction time. 599ms 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

Aim7.3

Positioning6.1

Utility4.0

Mechanics6.5

Opening Duels3.8

Win Impact0.0

Composite 5.4/10 (Developing), 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 rating-0.00−0.00

first ⅓ avg 0.00 → last ⅓ avg -0.00

Reaction time599ms+9ms

first ⅓ avg 590ms → last ⅓ avg 599ms

Headshot accuracy20.1%−1.0%

first ⅓ avg 21.1% → last ⅓ avg 20.1%

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

0.11Best rating — anubis 13–11

13–0Biggest win — nuke

3Longest win streak

W2Current streak

10–5In matches decided by ≤2 rounds

16Overtime games

Map breakdown

nukeBest map · 47% over 19overpassWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
inferno	D	26	6–20	23%	-0.00
nuke	B	19	9–10	47%	0.01
ancient	C	17	6–11	35%	0.00
anubis	B	13	6–7	46%	0.01
cache	C	11	4–7	36%	0.01
overpass	D	6	1–5	17%	-0.00
dust2	—	4	2–2	50%	0.02
eldorado	—	2	1–1	50%	-0.12
mirage	—	2	0–2	0%	-0.01

Across the last 100 tracked matches.

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

Faceit stats

Combat

900Matches

52%Win rate

1.30Avg K/D

83.5ADR

46%Headshot %

Clutches & streaks

44%1v1 clutch win

17%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	12	75%	1.59	18.7
Inferno	8	25%	0.90	14.6
Anubis	7	29%	0.94	16.7
Ancient	6	17%	0.78	15.2
Mirage	3	0%	0.76	13.0
Overpass	2	0%	0.68	10.0
Cache	1	0%	0.75	12.0
Dust2	1	0%	0.68	13.0

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.

20.5%Headshot accuracy

35.5%Accuracy (enemy spotted)

39.2%Spray accuracy

79.3%Counter-strafing

10.3°Preaim

599msReaction time

40.3%T opening success

50.5%CT opening success

0.58Enemies flashed / flash

6.4%Flash assists

6.96HE damage / grenade

3.81Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 3.8149 — below the 4 mark we flag
Grenade Lineups →

Spend your practice time on Overpass

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–6	-0.04	34%	27 Aug →
nuke	13–0	0.08	35%	27 Aug →
cache	15–15	0.03	15%	23 Aug →
inferno	13–8	0.08	16%	23 Aug →
inferno	15–15	-0.02	32%	22 Aug →
nuke	15–15	0.02	23%	21 Aug →
inferno	4–13	-0.05	31%	21 Aug →
ancient	16–14	0.02	13%	20 Aug →
inferno	3–13	-0.09	6%	20 Aug →
cache	13–3	0.04	33%	20 Aug →
eldorado	9–7	-0.06	14%	18 Aug →
nuke	10–13	0.04	20%	14 Aug →
ancient	1–13	-0.07	30%	14 Aug →
inferno	8–13	0.01	16%	13 Aug →
inferno	13–8	0.00	14%	13 Aug →
inferno	11–13	0.02	23%	12 Aug →
anubis	2–13	-0.08	18%	12 Aug →
inferno	13–16	-0.05	17%	3 Aug →
inferno	6–13	-0.01	21%	30 Jul →
inferno	15–15	0.05	27%	29 Jul →
inferno	6–13	-0.02	12%	29 Jul →
ancient	6–13	-0.10	14%	29 Jul →
nuke	13–9	-0.06	19%	29 Jul →
nuke	11–13	0.01	31%	26 Jul →
nuke	13–10	-0.02	20%	26 Jul →
mirage	7–13	-0.02	20%	26 Jul →
cache	10–13	0.02	14%	25 Jul →
inferno	5–13	0.03	29%	25 Jul →
cache	3–13	-0.04	11%	25 Jul →
anubis	13–11	0.11	17%	25 Jul →
anubis	4–13	0.06	11%	25 Jul →
anubis	13–6	0.01	12%	25 Jul →
cache	4–13	-0.04	17%	25 Jul →
anubis	8–13	0.03	16%	24 Jul →
ancient	13–10	0.03	18%	24 Jul →
cache	13–4	0.00	16%	24 Jul →
inferno	13–16	0.02	17%	24 Jul →
inferno	10–13	-0.02	9%	24 Jul →
eldorado	3–9	-0.18	14%	24 Jul →
ancient	12–16	0.01	19%	23 Jul →
nuke	13–2	0.08	33%	23 Jul →
inferno	12–16	0.01	16%	23 Jul →
inferno	6–13	0.03	32%	22 Jul →
cache	13–5	0.08	39%	22 Jul →
anubis	13–9	0.05	28%	22 Jul →
ancient	4–13	-0.03	27%	21 Jul →
inferno	16–14	0.05	22%	20 Jul →
nuke	9–13	-0.07	19%	20 Jul →
cache	12–16	0.07	23%	17 Jul →
cache	3–13	-0.03	30%	17 Jul →
anubis	8–13	-0.06	26%	16 Jul →
ancient	6–13	0.07	20%	15 Jul →
inferno	7–13	0.04	23%	15 Jul →
inferno	16–12	-0.00	26%	13 Jul →
nuke	13–11	-0.03	26%	13 Jul →
anubis	13–10	0.03	18%	13 Jul →
ancient	6–13	-0.05	10%	12 Jul →
anubis	8–13	-0.03	16%	12 Jul →
cache	13–10	-0.01	22%	12 Jul →
inferno	13–9	0.06	14%	12 Jul →
ancient	13–8	0.10	32%	1 Jul →
nuke	6–13	0.01	18%	28 Jun →
anubis	13–10	0.06	19%	28 Jun →
anubis	6–13	-0.04	17%	25 Jun →
overpass	10–13	0.01	20%	20 Jun →
dust2	13–8	0.06	23%	20 Jun →
ancient	13–16	-0.02	16%	19 Jun →
dust2	3–13	-0.01	18%	19 Jun →
nuke	14–16	0.02	25%	19 Jun →
nuke	13–2	0.04	24%	14 Jun →
ancient	6–13	-0.03	21%	14 Jun →
dust2	13–10	0.07	27%	13 Jun →
inferno	15–15	-0.02	27%	13 Jun →
ancient	0–13	-0.05	10%	9 Jun →
overpass	9–13	0.01	13%	9 Jun →
ancient	13–7	0.08	15%	9 Jun →
ancient	9–13	0.02	14%	4 Jun →
nuke	14–16	0.00	24%	4 Jun →
inferno	2–13	-0.06	12%	4 Jun →
ancient	13–7	0.05	14%	4 Jun →
nuke	13–11	0.05	31%	31 May →
overpass	6–13	-0.01	29%	30 May →
overpass	4–13	-0.02	22%	23 May →
inferno	4–13	-0.03	35%	23 May →
overpass	13–11	0.05	20%	22 May →
anubis	13–9	-0.06	20%	22 May →
ancient	5–13	-0.02	21%	22 May →
overpass	5–13	-0.05	19%	22 May →
nuke	13–11	0.02	11%	19 May →
inferno	9–13	0.01	18%	14 May →
ancient	13–11	-0.01	23%	14 May →
nuke	7–13	0.03	19%	14 May →
dust2	11–13	-0.05	19%	8 May →
inferno	6–13	-0.04	41%	6 May →
inferno	13–11	-0.03	21%	6 May →
nuke	7–13	0.02	24%	6 May →
cache	2–13	-0.01	13%	2 May →
anubis	9–13	0.00	13%	2 May →
nuke	9–13	0.08	34%	2 May →
mirage	9–13	-0.00	19%	1 May →