Sigurd — CS2 Stats

76561199268388408[U:1:1308122680]✓ No bans

628Tracked matches30%Win rate2023Tracked since

293Hours in CS

CSDB Rating3.9 LearningHybrid Rifler

WingmanGold Nova Master

Ladder ranks via Leetify

Performance scores

Aim60

Positioning43

Utility15

0–100 skill scores via Leetify.

Recent form

COLD48–46–6Last 10048%Win rateWLLLWLLLWL

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim6.0

Aggression4.8

Utility1.5

Positioning4.3

Opening Duels0.5

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 NiKo 77% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower aim profile; lower 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

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. 584ms 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

Aim6.0

Positioning4.3

Utility1.5

Mechanics6.7

Opening Duels0.5

Win Impact0.0

Composite 3.9/10 (Learning), 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-0.03−0.04

first ⅓ avg 0.01 → last ⅓ avg -0.03

Reaction time595ms+18ms

first ⅓ avg 578ms → last ⅓ avg 595ms

Headshot accuracy16.6%−0.8%

first ⅓ avg 17.5% → last ⅓ avg 16.6%

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.

Highlights

0.19Best rating — anubis 13–2

13–1Biggest win — inferno

5Longest win streak

6–8In matches decided by ≤2 rounds

9Overtime games

Map breakdown

anubisBest map · 62% over 13ancientWeakest map · 33% over 21

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	38	18–20	47%	-0.01
ancient	D	21	7–14	33%	-0.02
anubis	A	13	8–5	62%	0.01
dust2	A	11	6–5	55%	-0.02
mirage	A	9	5–4	56%	0.01
nuke	B	6	3–3	50%	-0.04
overpass	—	1	0–1	0%	-0.06
brewery	—	1	1–0	100%	0.04

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 21). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

9,716Lifetime kills

0.80K/D

723Matches

48.1%Match win rate · Top 50% of tracked players

44.1%Headshot %

2.8%Shot accuracy

1,238MVPs

293Hours (in match)

960Bombs planted

146Bombs defused

Most-used weapons

AK-473,842

M4A4 / M4A1-S1,937

AWP723

Desert Eagle695

P2000 / USP-S572

Glock-18567

MP9331

Galil AR207

MAC-10124

SSG 08123

Lifetime map wins

2,042inferno

916dust2

626vertigo

343nuke

70train

26office

8italy

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

16.9%Headshot accuracy

29.6%Accuracy (enemy spotted)

32.0%Spray accuracy

80.3%Counter-strafing

9.1°Preaim

584msReaction time

31.1%T opening success

33.1%CT opening success

0.45Enemies flashed / flash

9.5%Flash assists

9.05HE damage / grenade

1.48Flashes / 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
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4486 — below the 0.5 mark we flag
Grenade Lineups →
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 31.059% — below the 40% mark we flag

Spend your practice time on Ancient

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

33% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–9	-0.11	3%	28 Jul →
ancient	5–13	-0.12	17%	28 Jul →
anubis	9–13	-0.02	19%	21 Mar →
inferno	7–13	-0.02	13%	21 Mar →
mirage	13–2	0.04	17%	4 Oct →
inferno	11–13	-0.03	25%	4 Oct →
dust2	8–13	0.00	20%	4 Oct →
ancient	2–13	-0.07	12%	4 Oct →
inferno	13–6	-0.03	14%	28 Sept →
overpass	8–13	-0.06	9%	28 Sept →
inferno	5–13	-0.07	34%	14 Jul →
mirage	5–13	-0.07	14%	3 Jul →
ancient	13–7	-0.02	19%	3 Jul →
inferno	11–13	-0.02	14%	3 Jul →
ancient	3–13	0.00	16%	29 Jun →
inferno	11–13	-0.05	13%	28 Jun →
mirage	13–6	0.06	25%	28 Jun →
dust2	13–4	-0.07	15%	28 Jun →
ancient	11–13	-0.07	17%	28 Jun →
nuke	9–13	-0.05	13%	27 Jun →
inferno	13–11	0.02	18%	27 Jun →
anubis	10–13	-0.05	28%	27 Jun →
ancient	7–13	-0.06	18%	27 Jun →
anubis	13–6	0.05	20%	27 Jun →
inferno	9–13	-0.04	19%	24 Jun →
inferno	3–11	0.06	9%	23 Jun →
inferno	13–8	0.03	18%	14 Jun →
inferno	3–13	-0.08	17%	1 Jun →
inferno	6–13	-0.02	13%	29 May →
inferno	3–13	0.01	17%	23 May →
ancient	13–10	-0.06	11%	22 May →
inferno	9–5	-0.09	14%	18 May →
nuke	9–4	-0.02	21%	18 May →
inferno	10–13	-0.03	22%	18 May →
brewery	9–2	0.04	17%	17 May →
inferno	9–0	0.15	17%	17 May →
nuke	8–8	0.00	20%	17 May →
inferno	5–13	-0.01	23%	17 May →
inferno	13–11	-0.03	11%	16 May →
ancient	15–15	-0.03	4%	11 May →
dust2	13–8	-0.03	14%	11 May →
ancient	6–13	-0.03	16%	11 May →
inferno	13–11	0.02	20%	11 May →
anubis	13–8	-0.01	21%	11 May →
inferno	13–7	0.02	14%	11 May →
ancient	13–5	-0.00	14%	10 May →
dust2	13–5	0.03	12%	10 May →
inferno	10–13	-0.08	8%	9 May →
ancient	16–14	-0.05	15%	9 May →
anubis	15–15	-0.05	19%	9 May →
inferno	12–12	-0.07	10%	8 May →
anubis	13–7	0.00	14%	3 May →
mirage	9–13	-0.02	7%	3 May →
ancient	10–13	-0.06	15%	3 May →
inferno	14–16	-0.05	21%	3 May →
nuke	4–13	-0.05	14%	3 May →
inferno	13–1	0.09	9%	3 May →
inferno	5–0	0.04	8%	2 May →
inferno	7–13	-0.11	13%	30 Apr →
dust2	13–10	-0.00	12%	30 Apr →
ancient	13–6	-0.02	6%	30 Apr →
dust2	7–13	0.01	13%	30 Apr →
anubis	7–13	0.02	6%	29 Apr →
mirage	9–13	-0.02	14%	29 Apr →
dust2	13–4	0.05	13%	29 Apr →
ancient	6–13	-0.01	8%	28 Apr →
anubis	13–8	0.01	9%	28 Apr →
ancient	12–16	-0.04	6%	28 Apr →
inferno	13–1	-0.03	28%	27 Apr →
inferno	13–2	0.16	16%	27 Apr →
ancient	15–15	-0.00	9%	26 Apr →
dust2	13–11	-0.04	6%	26 Apr →
inferno	13–9	-0.07	9%	24 Apr →
inferno	7–13	-0.02	19%	24 Apr →
inferno	4–13	-0.09	19%	23 Apr →
mirage	13–4	0.02	19%	21 Apr →
ancient	15–15	0.00	20%	21 Apr →
inferno	13–5	0.03	23%	21 Apr →
inferno	4–0	0.07	17%	21 Apr →
inferno	13–6	0.04	14%	20 Apr →
ancient	14–16	-0.02	8%	20 Apr →
anubis	7–13	-0.02	16%	20 Apr →
inferno	13–8	0.05	20%	20 Apr →
nuke	13–7	-0.02	7%	19 Apr →
dust2	14–16	-0.03	20%	19 Apr →
anubis	13–7	0.01	20%	19 Apr →
anubis	13–6	-0.02	31%	19 Apr →
dust2	9–13	-0.06	12%	19 Apr →
mirage	13–11	-0.02	27%	19 Apr →
anubis	13–2	0.19	11%	19 Apr →
mirage	10–0	0.12	15%	19 Apr →
inferno	7–13	0.04	22%	19 Apr →
mirage	1–13	-0.04	24%	18 Apr →
inferno	8–13	0.01	17%	18 Apr →
inferno	13–2	-0.00	35%	18 Apr →
anubis	13–6	0.01	16%	17 Apr →
ancient	13–6	0.11	20%	17 Apr →
ancient	13–6	0.02	20%	17 Apr →
dust2	6–13	-0.04	10%	17 Apr →
ancient	11–13	0.07	24%	17 Apr →