MightyHugo — CS2 Stats

76561199174982478[U:1:1214716750]Steam profile ↗

143Tracked matches11%Win rate2023Tracked since

136Hours in CS

CSDB Rating1.4 Learning

Ladder ranks via Leetify

Performance scores

Aim4

Positioning23

Utility27

0–100 skill scores via Leetify.

Recent form

COLD28–69–3Last 10028%Win rateLLLLLLWLLL

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

Player DNA

Aim0.4

Aggression0.0

Utility2.7

Positioning2.3

Opening Duels0.0

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 50% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower opening-fight frequency; 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. 751ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 61% 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

Aim0.4

Positioning2.3

Utility2.7

Mechanics2.5

Opening Duels0.0

Win Impact0.0

Composite 1.4/10 (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-0.06+0.01

first ⅓ avg -0.07 → last ⅓ avg -0.06

Reaction time767ms+2ms

first ⅓ avg 765ms → last ⅓ avg 767ms

Headshot accuracy11.5%−2.8%

first ⅓ avg 14.2% → last ⅓ avg 11.5%

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

0.04Best rating — mirage 13–3

13–2Biggest win — anubis

4Longest win streak

L6Current streak

4–4In matches decided by ≤2 rounds

1Overtime games

Map breakdown

juraBest map · 40% over 5infernoWeakest map · 18% over 11

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	29	7–22	24%	-0.07
mirage	D	21	6–15	29%	-0.05
inferno	D	11	2–9	18%	-0.08
nuke	C	11	4–7	36%	-0.06
anubis	D	9	2–7	22%	-0.06
overpass	D	5	1–4	20%	-0.05
jura	C	5	2–3	40%	-0.06
vertigo	—	4	1–3	25%	-0.05
train	—	3	2–1	67%	-0.09
ancient	—	2	1–1	50%	-0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

5,591Lifetime kills

0.54K/D

565Matches

25.1%Match win rate

34.8%Headshot %

1.6%Shot accuracy

388MVPs

136Hours (in match)

306Bombs planted

50Bombs defused

Most-used weapons

M4A4 / M4A1-S1,277

AK-47828

AWP360

Desert Eagle261

Galil AR260

P2000 / USP-S247

MP7229

XM1014188

Negev179

MP9174

Lifetime map wins

586dust2

269vertigo

268inferno

179nuke

56train

8cbble

6assault

2office

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.

9.5%Headshot accuracy

25.0%Accuracy (enemy spotted)

24.8%Spray accuracy

61.2%Counter-strafing

16.0°Preaim

751msReaction time

7.5%T opening success

16.2%CT opening success

0.48Enemies flashed / flash

1.4%Flash assists

0.15HE damage / grenade

6.59Flashes / 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 15.9844° — above the 12° mark we flag
Aim Training →
Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 9.5141% — below the 15% mark we flag
Aim Training →
Best CS2 Settings
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 751.428ms — above the 700ms 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.

18% win rate across 11 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
inferno	1–13	-0.09	15%	25 Aug →
nuke	8–13	-0.03	4%	25 Aug →
mirage	8–13	-0.08	5%	25 Aug →
dust2	4–13	-0.02	8%	25 Aug →
dust2	0–13	-0.12	6%	23 Aug →
nuke	6–13	-0.08	3%	23 Aug →
nuke	13–9	-0.05	9%	22 Aug →
mirage	10–13	-0.01	14%	18 Apr →
anubis	10–13	-0.07	8%	9 Apr →
overpass	5–13	-0.09	7%	9 Apr →
anubis	12–12	-0.07	0%	2 Apr →
dust2	0–13	-0.05	8%	11 Mar →
mirage	6–13	-0.09	0%	8 Mar →
inferno	2–13	-0.11	11%	8 Mar →
dust2	5–13	-0.09	14%	8 Mar →
anubis	0–2	-0.03	0%	8 Mar →
nuke	5–13	-0.04	12%	6 Mar →
mirage	6–13	-0.03	16%	4 Mar →
mirage	7–13	-0.05	7%	4 Mar →
dust2	3–13	-0.10	0%	4 Mar →
dust2	0–4	-0.02	100%	1 Mar →
inferno	8–13	-0.09	11%	1 Mar →
dust2	13–11	-0.01	8%	1 Mar →
vertigo	7–13	-0.04	11%	27 Feb →
inferno	0–13	-0.10	33%	27 Feb →
overpass	3–13	-0.04	0%	27 Feb →
dust2	6–13	-0.08	18%	27 Feb →
dust2	12–12	-0.06	14%	27 Feb →
mirage	0–13	-0.06	6%	27 Feb →
dust2	13–7	-0.03	12%	26 Feb →
mirage	5–13	-0.03	3%	26 Feb →
nuke	13–11	-0.01	16%	26 Feb →
nuke	10–13	-0.07	0%	25 Feb →
nuke	13–5	-0.08	13%	25 Feb →
mirage	1–13	-0.08	13%	25 Feb →
dust2	4–13	-0.17	0%	18 Feb →
inferno	7–13	-0.05	4%	10 Feb →
dust2	7–13	-0.11	13%	10 Feb →
dust2	1–13	-0.08	0%	9 Feb →
anubis	10–13	-0.06	6%	3 Feb →
mirage	6–13	-0.01	4%	3 Feb →
inferno	9–13	-0.11	9%	2 Feb →
nuke	6–13	-0.09	8%	2 Feb →
anubis	13–10	-0.04	8%	2 Feb →
inferno	13–5	-0.05	19%	2 Feb →
overpass	3–13	-0.09	8%	30 Jan →
nuke	5–13	-0.03	2%	24 Jan →
dust2	2–13	-0.03	9%	24 Jan →
dust2	4–13	-0.06	22%	24 Jan →
anubis	13–2	-0.06	11%	24 Jan →
dust2	5–13	-0.10	6%	22 Jan →
dust2	0–13	-0.07	18%	22 Jan →
dust2	11–13	-0.04	8%	17 Jan →
dust2	10–13	-0.04	8%	17 Jan →
overpass	3–13	-0.03	8%	15 Jan →
overpass	13–8	-0.02	8%	14 Jan →
dust2	9–13	-0.04	9%	8 Jan →
mirage	12–12	-0.09	3%	9 Nov →
dust2	13–9	-0.07	6%	9 Nov →
train	9–13	-0.12	6%	9 Nov →
anubis	10–13	-0.06	8%	20 Aug →
dust2	10–13	-0.11	14%	15 Aug →
dust2	0–7	-0.10	50%	15 Aug →
train	13–4	-0.03	8%	15 Aug →
dust2	13–10	-0.00	13%	13 Aug →
mirage	11–13	-0.09	4%	13 Aug →
mirage	13–3	0.04	8%	13 Aug →
dust2	3–13	-0.10	8%	13 Aug →
dust2	13–8	-0.09	9%	12 Aug →
mirage	8–13	-0.04	13%	11 Aug →
jura	10–13	-0.04	8%	4 Aug →
mirage	13–2	-0.08	19%	4 Aug →
jura	13–8	-0.04	17%	4 Aug →
inferno	9–6	-0.09	8%	4 Aug →
jura	10–13	-0.11	7%	3 Aug →
inferno	1–13	-0.08	5%	3 Aug →
train	13–4	-0.13	8%	3 Aug →
jura	0–8	-0.06	20%	3 Aug →
mirage	2–13	0.01	11%	2 Aug →
dust2	13–11	-0.06	13%	2 Aug →
mirage	13–4	-0.03	13%	2 Aug →
nuke	13–6	-0.03	5%	30 Jul →
jura	13–7	-0.05	7%	30 Jul →
inferno	7–13	-0.08	4%	30 Jul →
dust2	13–4	-0.07	10%	2 Jul →
mirage	13–10	-0.08	8%	2 Jul →
anubis	9–13	-0.09	6%	29 Jun →
inferno	3–13	-0.04	22%	15 Apr →
ancient	6–13	-0.05	12%	15 Apr →
vertigo	1–13	-0.09	20%	11 Jan →
nuke	6–13	-0.10	10%	11 Jan →
mirage	10–13	-0.07	9%	11 Jan →
mirage	13–6	-0.01	21%	11 Jan →
anubis	0–4	-0.08	100%	8 Jan →
vertigo	13–7	-0.02	18%	8 Jan →
dust2	10–13	-0.06	24%	7 Jan →
ancient	13–11	-0.10	5%	7 Jan →
mirage	13–9	-0.05	13%	7 Jan →
mirage	6–13	-0.10	8%	7 Jan →
vertigo	14–16	-0.04	10%	7 Jan →