Matahari — CS2 Stats

76561198038991517[U:1:78725789]

593Tracked matches38%Win rate2020Tracked since
CSDB Rating3.1 Learning
Premier CS Rating11,582Blue band · top ~46.5% of ranked players (population est.)
CSDB Leaderboard#23371 of 33239 tracked
Ladder ranks via Leetify

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CSDB.GGMatahariPREMIER11,582 · Blue bandcsdb.gg/stats

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Performance scores

Aim36
Positioning33
Utility50

0–100 skill scores via Leetify.

Recent form

STEADY45487Last 10045%Win rateWLLLLWWLTW

Last 10 vs previous 10: -10pp win rate · -0.04 avg rating

Player DNA

Aim3.6
Aggression3.7
Utility5.0
Positioning3.3
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

NiKo

Plays most like NiKo 74% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower positioning profile; 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. 678ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% 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

Aim3.6
Positioning3.3
Utility5.0
Mechanics3.8
Opening Duels0.6
Win Impact1.0

Composite 3.1/10 (Learning), 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-0.02−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time678ms+17ms
first ⅓ avg 661ms → last ⅓ avg 678ms
Headshot accuracy18.5%+0.4%
first ⅓ avg 18.1% → last ⅓ avg 18.5%

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

0.17Best rating — office 7–13
131Biggest win — ancient
5Longest win streak
69In matches decided by ≤2 rounds

Map breakdown

dust2Best map · 71% over 7trainWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
cacheS1913668%-0.00
nukeC135838%-0.01
anubisD1221017%-0.04
ancientA127558%0.01
mirageC114736%-0.02
infernoA95456%0.01
trainD81713%-0.05
dust2S75271%-0.00
vertigoC52340%-0.01
office3030%0.04
overpass110100%-0.06

Across the last 100 tracked matches.

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
32.3%Accuracy (enemy spotted)
36.7%Spray accuracy
67.0%Counter-strafing
13.5°Preaim
678msReaction time
25.1%T opening success
34.4%CT opening success
0.49Enemies flashed / flash
4.0%Flash assists
6.69HE damage / grenade
14.12Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 13.5104° — above the 12° 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 0.4896 — below the 0.5 mark we flag

    Grenade Lineups
Spend your practice time on Train

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

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy

Recent matches

MapScoreRatingHS%Date
inferno13–6-0.0419%23 Aug
train8–8-0.1317%23 Aug
vertigo7–13-0.0822%23 Aug
anubis1–13-0.0621%23 Aug
anubis8–13-0.0911%12 Aug
cache13–50.0112%12 Aug
cache13–11-0.0319%3 Aug
cache8–13-0.0225%3 Aug
nuke12–120.0225%3 Aug
ancient13–90.0422%3 Aug
office11–130.0322%26 Jul
nuke11–130.0922%26 Jul
ancient13–6-0.048%26 Jul
cache9–13-0.0320%26 Jul
train8–130.0922%26 Jul
mirage13–5-0.0421%25 Jul
nuke13–7-0.0221%22 Jul
ancient7–13-0.0723%22 Jul
inferno8–0-0.0425%22 Jul
cache13–90.0519%22 Jul
anubis10–13-0.089%22 Jul
cache13–110.0115%9 Jul
anubis10–13-0.0417%9 Jul
ancient6–13-0.0318%9 Jul
mirage0–13-0.0513%9 Jul
mirage0–2-0.080%9 Jul
dust25–13-0.1124%9 Jul
nuke8–13-0.0115%9 Jul
office7–130.1728%9 Jul
overpass13–11-0.069%5 Jul
ancient9–13-0.0926%5 Jul
nuke11–13-0.0124%5 Jul
mirage5–13-0.0017%3 Jul
train1–13-0.1029%3 Jul
anubis13–50.0017%3 Jul
dust213–8-0.0217%2 Jul
cache0–13-0.1023%30 Jun
dust213–100.0523%27 Jun
mirage13–2-0.0315%27 Jun
vertigo13–100.0019%27 Jun
nuke6–13-0.1010%27 Jun
anubis11–13-0.0618%26 Jun
ancient13–20.0810%26 Jun
inferno5–130.0223%26 Jun
dust213–90.0426%26 Jun
ancient13–10.1013%22 Jun
inferno3–13-0.100%22 Jun
mirage13–10-0.0611%22 Jun
cache13–100.0619%17 Jun
ancient13–10.016%6 Jun
cache13–10.0213%6 Jun
nuke12–120.0120%6 Jun
nuke1–130.0425%5 Jun
anubis7–130.0120%4 Jun
ancient10–13-0.0017%4 Jun
cache13–110.0214%3 Jun
mirage8–130.0125%3 Jun
vertigo5–13-0.0126%3 Jun
inferno11–130.0614%2 Jun
ancient13–60.0212%2 Jun
dust213–5-0.0316%2 Jun
nuke13–40.0514%2 Jun
vertigo13–70.0016%2 Jun
anubis4–13-0.064%2 Jun
mirage4–130.0233%2 Jun
cache13–30.0117%2 Jun
cache13–5-0.0012%2 Jun
anubis9–13-0.0431%31 May
inferno13–30.1032%31 May
nuke5–13-0.0341%25 May
train9–13-0.0511%23 May
nuke13–4-0.0320%23 May
cache2–13-0.0315%23 May
dust25–13-0.0220%23 May
mirage13–20.1023%23 May
mirage6–13-0.0221%22 May
cache13–2-0.0118%22 May
dust213–30.0619%21 May
anubis11–13-0.059%21 May
train10–13-0.034%21 May
ancient8–130.0617%21 May
nuke13–9-0.0312%21 May
inferno13–20.0840%21 May
cache13–10.0433%21 May
anubis12–12-0.0715%21 May
train13–4-0.0218%20 May
cache12–120.0424%20 May
office10–13-0.0812%20 May
inferno4–130.0016%20 May
cache12–12-0.0411%20 May
cache13–2-0.0112%19 May
train12–12-0.0123%18 May
train0–2-0.150%18 May
ancient13–100.0718%18 May
anubis13–110.0824%18 May
nuke3–1-0.110%18 May
cache13–7-0.0323%18 May
inferno13–100.0213%18 May
vertigo12–120.0212%18 May
mirage9–13-0.079%18 May

Match data via Leetify.

Recent teammates

Milestones

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