[Tygo] — CS2 Stats

76561199173386896[U:1:1213121168]Steam profile ↗

227Tracked matches48%Win rate2022Tracked since

211Hours in CS3Hrs last 2 wks

CSDB Rating6.1 SolidHybrid Rifler

Ladder ranks via Leetify

Performance scores

Aim77

Positioning56

Utility49

0–100 skill scores via Leetify.

Recent form

STEADY49–47–4Last 10049%Win rateLWLWWWLLWW

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

Player DNA

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

Aim7.7

Aggression5.1

Utility4.9

Positioning5.6

Opening Duels2.9

Clutch5.4

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 90% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

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

Reaction time. 588ms 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

Aim7.7

Positioning5.6

Utility4.9

Mechanics8.0

Opening Duels2.9

Win Impact4.4

Composite 6.1/10 (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 rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time578ms−65ms

first ⅓ avg 643ms → last ⅓ avg 578ms

Headshot accuracy18.0%−1.7%

first ⅓ avg 19.7% → last ⅓ avg 18.0%

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

0.14Best rating — anubis 13–3

13–0Biggest win — mirage

4Longest win streak

7–5In matches decided by ≤2 rounds

5Overtime games

Map breakdown

ancientBest map · 67% over 15infernoWeakest map · 30% over 10

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	34	16–18	47%	0.00
ancient	S	15	10–5	67%	0.01
anubis	A	11	7–4	64%	0.06
inferno	D	10	3–7	30%	-0.02
dust2	A	9	5–4	56%	0.01
overpass	C	7	3–4	43%	0.04
nuke	A	5	3–2	60%	-0.02
train	—	4	1–3	25%	-0.02
cache	—	3	1–2	33%	-0.02
poseidon	—	1	0–1	0%	-0.04
grail	—	1	0–1	0%	0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

5,769Lifetime kills

1.08K/D · Top 50% of tracked players

336Matches

45.8%Match win rate

49.1%Headshot % · Top 50% of tracked players

4.4%Shot accuracy

817MVPs

121Hours (in match)

424Bombs planted

81Bombs defused

Most-used weapons

AK-472,415

M4A4 / M4A1-S923

AWP367

P2000 / USP-S352

Glock-18312

Desert Eagle232

P90162

MP9130

MAC-10111

Nova106

Lifetime map wins

375inferno

279dust2

248nuke

130vertigo

77train

17cbble

2office

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

Faceit stats

Combat

31Matches

48%Win rate

1.13Avg K/D

77.3ADR

41%Headshot %

Clutches & streaks

47%1v1 clutch win

20%1v2 clutch win

4Longest win streak

Recent Faceit resultsWWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	8	75%	1.09	15.4
Mirage	8	25%	0.71	11.5
Anubis	5	80%	2.24	19.8
Dust2	4	25%	1.13	16.8
Inferno	3	33%	0.92	15.3
Nuke	2	50%	0.73	11.5
Overpass	1	0%	0.78	14.0

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.

18.5%Headshot accuracy

37.1%Accuracy (enemy spotted)

40.9%Spray accuracy

86.2%Counter-strafing

10.9°Preaim

588msReaction time

38.0%T opening success

45.5%CT opening success

0.67Enemies flashed / flash

6.9%Flash assists

5.48HE damage / grenade

10.29Flashes / 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 37.9769% — below the 40% mark we flag

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.

30% win rate across 10 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	10–13	-0.05	17%	15 Aug →
anubis	13–8	0.05	13%	15 Aug →
anubis	3–13	-0.03	28%	14 Aug →
mirage	5–2	0.13	28%	14 Aug →
mirage	13–7	0.05	12%	5 Aug →
dust2	13–6	0.05	15%	26 Jul →
ancient	8–13	-0.07	7%	24 Jul →
cache	11–13	-0.02	6%	10 Jul →
dust2	13–11	0.01	22%	10 Jul →
cache	13–4	-0.04	24%	8 Jun →
mirage	0–13	-0.02	30%	24 May →
dust2	15–15	0.02	20%	22 May →
ancient	13–9	-0.05	17%	22 May →
anubis	13–6	0.03	24%	2 May →
overpass	11–2	0.10	14%	2 May →
cache	11–13	0.00	32%	2 May →
ancient	13–5	-0.02	7%	9 Apr →
anubis	11–13	0.04	17%	7 Apr →
nuke	7–13	-0.03	30%	7 Apr →
ancient	13–3	0.08	12%	7 Apr →
anubis	13–3	0.14	7%	7 Apr →
train	6–13	-0.01	8%	6 Apr →
mirage	8–13	-0.05	14%	30 Mar →
inferno	7–13	-0.06	21%	29 Mar →
ancient	14–16	-0.02	22%	27 Mar →
overpass	13–1	0.08	21%	27 Mar →
dust2	9–13	0.02	16%	25 Mar →
anubis	13–3	0.02	27%	24 Mar →
mirage	4–13	-0.02	14%	22 Mar →
nuke	7–13	-0.05	35%	22 Mar →
mirage	5–13	-0.06	12%	22 Mar →
mirage	10–13	-0.04	12%	17 Mar →
ancient	19–17	-0.05	9%	17 Mar →
poseidon	4–9	-0.04	5%	17 Mar →
inferno	3–9	-0.08	40%	17 Mar →
ancient	8–13	0.01	10%	16 Mar →
ancient	13–4	0.02	16%	16 Mar →
anubis	13–2	0.04	13%	15 Mar →
anubis	13–4	0.09	20%	15 Mar →
mirage	16–13	-0.01	13%	15 Mar →
mirage	9–13	-0.02	9%	15 Mar →
mirage	10–13	-0.02	10%	14 Mar →
ancient	13–6	0.10	21%	14 Mar →
nuke	13–11	-0.08	10%	14 Mar →
mirage	13–10	0.06	19%	11 Mar →
mirage	13–4	0.05	13%	10 Mar →
ancient	10–13	-0.04	16%	8 Mar →
mirage	3–13	-0.08	33%	8 Mar →
inferno	13–6	0.01	14%	7 Mar →
mirage	8–13	0.09	16%	7 Mar →
mirage	12–12	0.01	13%	7 Mar →
mirage	13–7	-0.07	4%	6 Mar →
mirage	13–8	-0.07	16%	4 Mar →
overpass	7–13	0.02	10%	1 Mar →
anubis	12–12	0.08	14%	1 Mar →
anubis	13–7	0.07	16%	28 Feb →
mirage	13–5	0.01	14%	21 Jan →
dust2	13–8	-0.01	21%	21 Jan →
mirage	6–13	-0.00	17%	2 Jan →
overpass	9–13	0.08	19%	20 Dec →
mirage	13–10	0.05	9%	20 Dec →
inferno	10–13	-0.01	7%	8 Dec →
mirage	8–13	-0.03	18%	22 Nov →
dust2	8–13	-0.04	15%	21 Nov →
inferno	6–13	-0.01	17%	21 Nov →
inferno	13–11	-0.06	13%	9 Nov →
overpass	13–8	0.03	9%	9 Nov →
train	13–5	-0.04	23%	9 Nov →
mirage	13–10	0.03	17%	9 Nov →
dust2	6–13	0.01	18%	4 Nov →
dust2	13–10	0.04	27%	4 Nov →
nuke	13–10	0.07	31%	2 Nov →
ancient	16–13	0.02	16%	2 Nov →
ancient	13–5	0.12	19%	2 Nov →
inferno	9–13	0.03	21%	2 Nov →
mirage	4–13	-0.03	11%	2 Nov →
ancient	5–13	0.00	29%	2 Nov →
mirage	13–8	-0.06	8%	2 Nov →
mirage	13–10	0.01	24%	27 Oct →
mirage	13–2	-0.01	40%	27 Oct →
mirage	7–13	-0.01	18%	26 Oct →
inferno	13–7	0.05	11%	26 Oct →
train	9–13	-0.02	34%	26 Oct →
mirage	8–13	-0.04	8%	26 Oct →
mirage	5–13	0.03	11%	24 Oct →
mirage	8–13	-0.03	10%	23 Aug →
ancient	13–11	-0.04	10%	22 Aug →
mirage	4–13	-0.02	21%	17 May →
grail	9–13	0.00	13%	11 May →
dust2	13–11	-0.01	23%	5 May →
mirage	13–7	0.06	26%	26 Apr →
overpass	4–9	-0.04	25%	21 Apr →
mirage	13–0	0.13	34%	21 Apr →
train	5–13	0.00	31%	10 Apr →
nuke	13–10	-0.03	3%	5 Apr →
anubis	11–13	0.09	18%	15 Mar →
ancient	13–11	0.02	24%	15 Mar →
overpass	8–13	0.00	20%	14 Mar →
mirage	13–9	0.03	16%	14 Mar →
inferno	8–8	-0.07	11%	12 Mar →