Feedbacc — CS2 Stats

76561198860929098[U:1:900663370]

79Tracked matches46%Win rate2026Tracked since
CSDB Rating5.2 DevelopingAggressive Rifler
Premier CS Rating14,664Blue band · top ~30.2% of ranked players (population est.)
CSDB Leaderboard#22064 of 34963 tracked
Ladder ranks via Leetify

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CSDB.GGFeedbaccPREMIER14,664 · Blue bandcsdb.gg/stats

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Performance scores

Aim77
Positioning61
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY36394Last 7946%Win rateLLWLLLLWWW

Last 10 vs previous 10: +0pp win rate · -0.07 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim7.7
Aggression7.2
Utility4.6
Positioning6.1
Opening Duels2.7

Strong CT-side openerEffective flashesLimited 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.

Your pro match

ropz

Plays most like ropz 90% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

Where you differ: lower opening-duel success; 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

Strengths

Flashes. 0.88 enemies blinded per flash — utility that consistently lands.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 52% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

Counter-strafing. Only 68% 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

Aim7.7
Positioning6.1
Utility4.6
Mechanics4.1
Opening Duels2.8
Win Impact3.8

Composite 5.2/10 (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 rating0.03+0.05
first ⅓ avg -0.02 → last ⅓ avg 0.03
Reaction time484ms−277ms
first ⅓ avg 761ms → last ⅓ avg 484ms
Headshot accuracy13.5%−1.6%
first ⅓ avg 15.2% → last ⅓ avg 13.5%

Rolling 5-match average across the last 79 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.34Best rating — cache 7–6
130Biggest win — ancient
7Longest win streak
L2Current streak
54In matches decided by ≤2 rounds
6Overtime games

Map breakdown

ancientBest map · 71% over 7infernoWeakest map · 20% over 10
MapGradePlayedRecordWin rateAvg rating
dust2C2191243%-0.01
mirageB168850%0.04
nukeA127558%0.01
infernoD102820%-0.01
ancientS75271%0.05
overpassD51420%-0.03
cache41325%0.15
anubis21150%-0.01
warden110100%0.06
office110100%0.03

Across the last 79 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.9%Headshot accuracy
39.6%Accuracy (enemy spotted)
36.7%Spray accuracy
68.4%Counter-strafing
8.7°Preaim
477msReaction time
29.5%T opening success
52.2%CT opening success
0.88Enemies flashed / flash
10.7%Flash assists
14.00HE damage / grenade
4.94Flashes / 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 14.8504% — below the 15% mark we flag

    Aim Training
  2. 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 29.528% — 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.

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
mirage0–10-0.120%11 Aug
dust21–13-0.100%7 Jul
dust23–3-0.040%7 Jul
ancient11–130.0120%24 Jun
dust28–13-0.0225%24 Jun
dust210–130.0714%20 Jun
nuke4–12-0.070%9 Jun
dust213–40.0420%4 Jun
nuke13–60.0911%3 Jun
warden13–40.0619%3 Jun
dust212–16-0.0512%2 Jun
cache7–60.3418%31 May
dust213–80.0510%31 May
dust28–13-0.0020%31 May
nuke13–100.0616%31 May
cache12–120.1520%31 May
overpass2–13-0.0119%31 May
ancient16–14-0.0215%31 May
mirage5–130.0011%30 May
mirage13–110.0513%30 May
overpass4–13-0.026%30 May
mirage13–90.0624%30 May
nuke12–120.124%29 May
dust27–30.019%29 May
mirage13–110.0010%29 May
ancient13–00.1138%29 May
inferno11–130.1124%28 May
nuke16–130.0717%28 May
nuke4–130.0016%28 May
mirage6–130.1311%28 May
dust210–130.0518%28 May
mirage5–130.156%28 May
mirage13–160.1013%28 May
mirage13–30.127%28 May
office13–00.0317%28 May
ancient13–40.109%27 May
mirage16–120.0413%27 May
anubis13–100.0313%27 May
overpass13–10-0.0011%27 May
nuke15–150.0529%27 May
ancient13–40.1112%26 May
ancient13–100.0115%26 May
mirage13–90.0817%26 May
mirage8–40.0350%26 May
inferno13–50.0814%26 May
inferno13–60.1815%26 May
nuke13–50.0420%26 May
dust26–13-0.0112%26 May
mirage8–130.0031%26 May
inferno8–13-0.1121%24 May
nuke0–13-0.1121%23 May
mirage2–13-0.0810%23 May
inferno4–13-0.0313%23 May
nuke13–6-0.046%23 May
overpass3–13-0.0619%22 May
anubis6–13-0.069%22 May
mirage3–130.0216%21 May
dust213–90.0715%21 May
dust213–6-0.0225%20 May
mirage13–10.057%20 May
nuke13–7-0.045%19 May
dust21–130.0220%14 May
dust24–130.0123%14 May
inferno4–130.0013%13 May
overpass1–10-0.0614%10 May
dust213–9-0.0315%7 May
cache13–100.1522%7 May
cache10–13-0.0411%7 May
dust211–13-0.067%28 Apr
dust23–13-0.0925%26 Apr
nuke13–8-0.0618%24 Apr
dust213–11-0.0417%17 Apr
inferno2–9-0.180%17 Apr
inferno5–9-0.035%16 Apr
inferno2–9-0.0813%14 Apr
dust213–100.0124%13 Apr
inferno6–9-0.0026%12 Apr
ancient12–120.0118%11 Apr
dust23–13-0.0522%11 Apr

Match data via Leetify.

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