Tizzo'sBigToe — CS2 Stats

76561199884093985[U:1:1923828257]

840Tracked matches52%Win rate2026Tracked since

907Hours in CS32Hrs last 2 wks

CSDB Rating4.7 DevelopingClutch Specialist

Premier CS Rating11,995Blue band · top ~44.3% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim59

Positioning59

Utility27

0–100 skill scores via Leetify.

Recent form

STEADY55–35–10Last 10055%Win rateWWLLLLWWTL

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

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim5.9

Aggression9.0

Utility2.7

Positioning5.9

Opening Duels4.0

Clutch10.0

Strong T-side openerLimited utility dependenceReliable in 1v1s

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 jL 83% playstyle similarity

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

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.

CT openings. Opening success drops from 56% on T to 37% on CT — first contacts on the defending side are being lost.

Reaction time. 605ms 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

Aim5.9

Positioning5.9

Utility2.7

Mechanics4.5

Opening Duels4.0

Win Impact5.6

Composite 4.7/10 (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 rating-0.01−0.03

first ⅓ avg 0.03 → last ⅓ avg -0.01

Reaction time603ms−75ms

first ⅓ avg 677ms → last ⅓ avg 603ms

Headshot accuracy13.7%−2.3%

first ⅓ avg 16.0% → last ⅓ avg 13.7%

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

0.18Best rating — dust2 13–0

13–0Biggest win — dust2

7Longest win streak

W2Current streak

5–6In matches decided by ≤2 rounds

Map breakdown

anubisBest map · 80% over 5infernoWeakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	30	17–13	57%	0.01
mirage	B	16	8–8	50%	0.02
nuke	C	12	5–7	42%	0.00
cache	S	12	8–4	67%	0.02
inferno	C	8	3–5	38%	-0.01
train	B	8	4–4	50%	0.03
ancient	S	6	4–2	67%	-0.02
anubis	S	5	4–1	80%	0.02
vertigo	—	2	1–1	50%	-0.06
office	—	1	1–0	100%	0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

15,672Lifetime kills

0.93K/D

1,102Matches

45.2%Match win rate

41.8%Headshot %

0.0%Shot accuracy

1,677MVPs

379Hours (in match)

1,509Bombs planted

298Bombs defused

Most-used weapons

AK-476,008

M4A4 / M4A1-S4,050

P2000 / USP-S894

Glock-18738

AWP735

Desert Eagle640

MAG-7254

MP9224

Galil AR188

MP7181

Lifetime map wins

2,239dust2

1,106nuke

750inferno

458vertigo

401train

39office

26italy

8ar_shoots

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

Faceit stats

Combat

1Matches

100%Win rate

4.17Avg K/D

131.9ADR

28%Headshot %

Clutches & streaks

100%1v1 clutch win

50%1v2 clutch win

1Longest win streak

Recent Faceit resultsLLLLW

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.

13.5%Headshot accuracy

34.7%Accuracy (enemy spotted)

36.3%Spray accuracy

70.2%Counter-strafing

8.2°Preaim

605msReaction time

55.5%T opening success

36.5%CT opening success

0.58Enemies flashed / flash

7.0%Flash assists

4.19HE damage / grenade

1.99Flashes / 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.

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 13.545% — below the 15% mark we flag
Aim Training →
Grenades & Utility
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 1.9866 — below the 4 mark we flag
Grenade Lineups →
Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 36.5326% — 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.

38% win rate across 8 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	13–9	-0.04	9%	22 Aug →
dust2	13–2	0.00	21%	22 Aug →
nuke	7–13	0.01	21%	21 Aug →
vertigo	5–13	-0.07	18%	21 Aug →
cache	6–13	-0.07	8%	21 Aug →
mirage	6–13	0.02	17%	21 Aug →
nuke	13–10	0.05	16%	21 Aug →
cache	13–6	0.04	9%	21 Aug →
dust2	12–12	-0.00	17%	20 Aug →
mirage	2–13	-0.07	8%	20 Aug →
dust2	13–7	-0.05	8%	20 Aug →
cache	13–7	0.03	10%	20 Aug →
ancient	13–8	0.01	21%	19 Aug →
anubis	12–12	0.03	11%	19 Aug →
mirage	13–4	0.05	19%	19 Aug →
ancient	11–13	-0.05	17%	19 Aug →
dust2	11–13	0.03	13%	19 Aug →
mirage	8–13	0.04	11%	19 Aug →
ancient	6–13	-0.08	13%	18 Aug →
cache	2–13	-0.03	15%	18 Aug →
dust2	13–11	-0.02	8%	17 Aug →
train	3–13	0.05	13%	17 Aug →
inferno	12–12	-0.02	13%	17 Aug →
dust2	13–11	-0.01	17%	17 Aug →
nuke	10–13	0.01	11%	16 Aug →
inferno	6–13	-0.05	12%	16 Aug →
dust2	13–5	-0.01	21%	15 Aug →
train	13–9	-0.02	12%	15 Aug →
mirage	13–2	0.06	8%	15 Aug →
cache	13–2	0.04	9%	15 Aug →
ancient	13–8	-0.04	13%	15 Aug →
dust2	13–11	0.02	15%	15 Aug →
nuke	13–10	-0.04	17%	15 Aug →
train	11–13	-0.02	9%	15 Aug →
cache	13–9	-0.01	15%	14 Aug →
nuke	5–13	-0.03	18%	14 Aug →
inferno	5–13	0.01	6%	14 Aug →
mirage	13–1	0.06	10%	14 Aug →
mirage	10–13	-0.07	12%	14 Aug →
dust2	5–13	-0.04	11%	14 Aug →
nuke	11–13	-0.06	19%	13 Aug →
dust2	13–9	-0.03	15%	13 Aug →
cache	13–2	0.04	9%	13 Aug →
nuke	12–12	0.06	9%	13 Aug →
mirage	13–9	-0.02	17%	13 Aug →
vertigo	13–10	-0.05	14%	13 Aug →
anubis	13–9	0.03	9%	12 Aug →
ancient	13–3	0.03	3%	12 Aug →
dust2	10–3	0.07	10%	12 Aug →
inferno	9–13	0.00	17%	12 Aug →
dust2	9–13	-0.06	16%	12 Aug →
train	12–12	0.01	19%	12 Aug →
dust2	3–13	-0.02	21%	11 Aug →
mirage	9–13	-0.01	13%	11 Aug →
dust2	13–8	-0.06	14%	11 Aug →
ancient	13–9	-0.01	13%	11 Aug →
dust2	13–11	-0.00	11%	11 Aug →
dust2	11–13	0.01	8%	10 Aug →
nuke	12–12	0.06	12%	10 Aug →
dust2	13–2	0.07	20%	10 Aug →
inferno	8–13	-0.05	4%	10 Aug →
mirage	13–10	0.13	11%	10 Aug →
anubis	13–9	-0.01	16%	10 Aug →
nuke	13–5	-0.01	14%	9 Aug →
mirage	12–12	0.06	18%	9 Aug →
cache	13–5	-0.01	23%	9 Aug →
dust2	10–3	0.05	19%	9 Aug →
dust2	3–13	-0.06	21%	9 Aug →
mirage	13–5	0.13	30%	9 Aug →
cache	6–13	0.04	15%	9 Aug →
mirage	6–13	-0.05	21%	9 Aug →
dust2	13–6	0.08	18%	9 Aug →
cache	13–4	0.07	15%	9 Aug →
dust2	12–12	-0.02	13%	8 Aug →
dust2	9–13	0.02	7%	8 Aug →
dust2	13–8	0.08	13%	8 Aug →
nuke	13–11	-0.08	8%	8 Aug →
dust2	12–12	-0.01	13%	7 Aug →
office	13–8	0.03	20%	7 Aug →
inferno	13–10	-0.03	20%	7 Aug →
train	13–5	0.13	8%	7 Aug →
train	13–1	0.02	24%	7 Aug →
dust2	13–9	0.02	23%	7 Aug →
dust2	13–3	0.02	13%	7 Aug →
mirage	13–8	0.00	15%	7 Aug →
cache	11–13	0.08	21%	7 Aug →
train	10–13	0.03	19%	7 Aug →
mirage	12–12	0.00	10%	7 Aug →
dust2	8–13	0.04	21%	7 Aug →
nuke	7–13	-0.07	3%	7 Aug →
mirage	13–7	0.03	12%	7 Aug →
dust2	13–0	0.18	21%	7 Aug →
inferno	13–5	0.10	19%	7 Aug →
anubis	13–5	0.01	8%	6 Aug →
dust2	10–13	-0.06	18%	6 Aug →
cache	13–9	-0.01	14%	6 Aug →
train	13–2	0.02	17%	6 Aug →
anubis	13–9	0.04	14%	6 Aug →
dust2	7–13	0.04	17%	5 Aug →
nuke	13–8	0.11	18%	5 Aug →