Toni

Toni — CS2 Stats

FI76561198995882662[U:1:1035616934]Steam profile ↗✓ No bans

404Tracked matches55%Win rate2020Tracked since
CSDB Rating4.9 DevelopingPositional Player
Premier CS Rating13,706Blue band · top ~35.3% of ranked players (population est.)
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 17 Oct 2026 (20 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 13,706 +140 1 Aug – 17 Oct · 8 days played
12,56614,709peak 14,7091 Aug17 Oct
14,709Peak Premier in tracked matches
41Days played since 2026-01-16

Premier CS Rating

  • 1,003 below peak (14,709)
  • -1,003 over 30 days · declining
  • +140 over 90 days
  • Next: Purple band at 15,000 — 1,294 to go
  • Reached: Blue band · Light Blue band

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Share this profile

CSDB.GGToniFACEITLevel 5STANDINGTop 67.6% of rankedPREMIER13,706 · Blue bandcsdb.gg/stats

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Performance scores

Aim61
Positioning47
Utility44

0–100 skill scores via Leetify.

Recent form

STEADY40–54–6Last 10040%Win rateWWWWLLLLLL

Last 10 vs previous 10: −10pp win rate · −0.05 avg rating · −5.5pp headshot accuracy · −32ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 623ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 11%
  • Avg reaction 611ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 627ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+2.3 against its own average).

Aim6.1
Utility4.4
Positioning4.7
Opening Duels0.6
Clutch0.0

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.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

iM

Plays most like iM 87% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-duel success.

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. 639ms 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

Aim6.1
Positioning4.7
Utility4.4
Mechanics6.6
Opening Duels0.5
Win Impact6.7

Composite 4.9/10 (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-0.00+0.02
first ⅓ avg -0.02 → last ⅓ avg -0.00
Reaction time649ms−42ms
first ⅓ avg 691ms → last ⅓ avg 649ms
Headshot accuracy14.1%+1.5%
first ⅓ avg 12.6% → last ⅓ avg 14.1%

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.

Personal bests

0.15Best match rating · 10–13 · ancient, 21 Aug →
33%Best headshot accuracy · 1–5 · mirage, 10 Aug →
414msFastest reaction time · 5–13 · inferno, 5 Sept →
13–1Biggest win · mirage, 5 Jul →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W4Current streak
2–5In matches decided by ≤2 rounds
5Overtime games

Map breakdown

mirageBest map · 78% over 9ancientWeakest map · 14% over 14
MapGradePlayedRecordWin rateAvg rating
cacheA2212–1055%-0.02
nukeC198–1142%-0.01
ancientD142–1214%-0.03
dust2C135–838%-0.01
infernoC125–742%-0.02
mirageS97–278%0.02
anubisD61–517%-0.03
overpass—20–20%-0.04
vertigo—10–10%-0.03
office—10–10%0.03
train—10–10%-0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (14% over 14). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

64Matches
53%Win rate
1.33Avg K/D
61.9ADR
33%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
8Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno450%1.0613.8
Nuke367%1.1611.7
Ancient367%0.719.7
Mirage250%0.9012.5
Anubis1100%1.2421.0
Train10%0.6111.0

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.

13.9%Headshot accuracy
33.9%Accuracy (enemy spotted)
36.8%Spray accuracy
79.5%Counter-strafing
8.7°Preaim
639msReaction time
27.5%T opening success
33.7%CT opening success
0.41Enemies flashed / flash
3.1%Flash assists
12.80HE damage / grenade
4.30Flashes / 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.

  1. 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 13.8779% — below the 15% mark we flag

    Aim Training →
  2. 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 0.4094 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 27.5182% — 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.

14% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–9-0.0612%17 Oct →
inferno13–8-0.047%12 Sept →
cache13–11-0.0314%12 Sept →
dust213–50.047%12 Sept →
ancient9–13-0.0220%12 Sept →
nuke5–13-0.0716%12 Sept →
dust28–13-0.0513%11 Sept →
inferno7–13-0.014%11 Sept →
vertigo11–13-0.0311%5 Sept →
inferno5–13-0.074%5 Sept →
overpass3–13-0.0517%5 Sept →
dust213–40.0018%5 Sept →
nuke13–5-0.0213%5 Sept →
ancient7–130.0522%5 Sept →
nuke13–8-0.018%21 Aug →
mirage13–90.0420%21 Aug →
ancient10–130.1517%21 Aug →
nuke7–130.0114%20 Aug →
inferno6–130.029%20 Aug →
nuke13–90.0124%20 Aug →
inferno16–12-0.0215%15 Aug →
dust213–3-0.0313%15 Aug →
mirage13–70.0813%15 Aug →
mirage1–5-0.0133%10 Aug →
inferno13–7-0.0313%1 Aug →
nuke13–50.0123%1 Aug →
anubis15–15-0.072%1 Aug →
inferno13–30.019%1 Aug →
nuke13–40.1026%1 Aug →
anubis10–13-0.0118%31 Jul →
dust28–130.0610%31 Jul →
nuke6–13-0.027%31 Jul →
ancient15–15-0.0312%31 Jul →
cache11–13-0.042%17 Jul →
mirage13–100.0416%17 Jul →
nuke8–13-0.0910%16 Jul →
ancient9–13-0.0913%16 Jul →
cache13–4-0.0119%16 Jul →
ancient5–13-0.0814%15 Jul →
nuke6–13-0.045%15 Jul →
cache13–20.0313%15 Jul →
cache13–70.0115%15 Jul →
cache10–13-0.0620%12 Jul →
inferno1–13-0.0522%12 Jul →
ancient1–13-0.0812%12 Jul →
cache11–13-0.0515%11 Jul →
cache13–80.099%11 Jul →
dust25–13-0.0410%11 Jul →
anubis13–70.0217%9 Jul →
cache10–13-0.078%7 Jul →
mirage16–120.0314%5 Jul →
dust216–140.0315%5 Jul →
mirage13–10.0119%5 Jul →
dust25–130.0424%29 Jun →
office9–130.038%29 Jun →
nuke2–13-0.0114%29 Jun →
dust210–13-0.0421%27 Jun →
nuke7–13-0.0218%23 Jun →
overpass1–9-0.0311%18 Jun →
anubis11–13-0.0415%15 Jun →
inferno13–10-0.0314%14 Jun →
nuke13–100.0211%13 Jun →
ancient13–9-0.0417%13 Jun →
cache12–12-0.0316%12 Jun →
cache8–130.018%12 Jun →
inferno4–13-0.037%1 Jun →
anubis7–13-0.038%1 Jun →
cache11–130.0413%30 May →
inferno12–120.017%29 May →
ancient4–13-0.049%29 May →
cache8–13-0.0113%23 May →
cache13–7-0.0116%23 May →
dust29–13-0.045%15 May →
cache13–10-0.0418%15 May →
ancient13–8-0.0723%15 May →
cache12–12-0.0511%15 May →
cache13–80.0217%15 May →
cache10–13-0.037%15 May →
cache13–6-0.005%15 May →
cache13–6-0.0224%7 May →
cache13–8-0.0213%7 May →
inferno5–13-0.0220%17 Apr →
ancient2–13-0.0619%2 Apr →
nuke13–90.027%2 Apr →
mirage13–70.0012%2 Apr →
nuke3–13-0.0321%1 Apr →
ancient12–12-0.076%1 Apr →
mirage13–10.0317%1 Apr →
nuke13–70.1519%28 Mar →
nuke8–13-0.049%28 Mar →
mirage8–13-0.0211%28 Mar →
train4–13-0.0112%27 Feb →
anubis7–13-0.0612%27 Feb →
dust23–13-0.067%27 Feb →
nuke9–13-0.0518%27 Feb →
ancient10–13-0.076%27 Feb →
ancient8–130.0511%14 Feb →
nuke9–13-0.100%11 Feb →
dust22–13-0.0513%17 Jan →
dust213–80.0014%16 Jan →

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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