Fram

Fram — CS2 Stats

US76561198289564718[U:1:329298990]Steam profile ↗✓ No bans

280Tracked matches53%Win rate2020Tracked since
CSDB Rating5.1 Developing
Premier CS Rating10,867Blue band · top ~50.3% of ranked players (population est.)
CSDB Leaderboard#20891 of 29203 tracked
WingmanGold Nova II
Ladder ranks via Leetify

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CSDB.GGFramPREMIER10,867 · Blue bandcsdb.gg/stats

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Performance scores

Aim59
Positioning63
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY46486Last 10046%Win rateLWLLWWWWLW

Last 10 vs previous 10: -10pp win rate · -0.03 avg rating

Player DNA

Aim5.9
Aggression9.4
Utility3.8
Positioning6.3
Opening Duels4.5

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

sh1ro

Plays most like sh1ro 86% playstyle similarity

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

Where you differ: lower utility contribution; 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. 649ms 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
Positioning6.3
Utility3.8
Mechanics4.8
Opening Duels4.5
Win Impact6.1

Composite 5.1/10 (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 rating0.00+0.01
first ⅓ avg -0.00 → last ⅓ avg 0.00
Reaction time660ms−46ms
first ⅓ avg 707ms → last ⅓ avg 660ms
Headshot accuracy15.4%−2.6%
first ⅓ avg 18.0% → last ⅓ avg 15.4%

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

0.16Best rating — inferno 13–8
132Biggest win — dust2
5Longest win streak
73In matches decided by ≤2 rounds
10Overtime games

Map breakdown

anubisBest map · 80% over 5infernoWeakest map · 25% over 16
MapGradePlayedRecordWin rateAvg rating
mirageB21111052%0.00
dust2A2112957%0.00
infernoD1641225%0.00
ancientA148657%-0.00
nukeD124833%-0.00
anubisS54180%0.03
overpass41325%-0.02
cache31233%-0.02
train3030%-0.05
office110100%-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 16). 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.

15.4%Headshot accuracy
37.5%Accuracy (enemy spotted)
42.4%Spray accuracy
71.4%Counter-strafing
11.0°Preaim
649msReaction time
46.9%T opening success
49.3%CT opening success
0.61Enemies flashed / flash
8.6%Flash assists
8.34HE damage / grenade
2.60Flashes / 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. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 2.6039 — below the 4 mark we flag

    Grenade Lineups
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.

25% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
ancient7–13-0.0213%27 Aug
mirage13–30.0723%27 Aug
inferno12–16-0.0418%27 Aug
mirage2–9-0.0817%27 Aug
dust213–8-0.0119%25 Aug
inferno13–80.0511%25 Aug
anubis13–90.0414%24 Aug
anubis13–110.0121%24 Aug
nuke11–13-0.0221%23 Aug
cache13–3-0.068%23 Aug
dust213–3-0.0315%23 Aug
ancient13–40.0421%23 Aug
ancient13–16-0.0323%23 Aug
nuke13–8-0.0214%23 Aug
mirage13–3-0.0313%23 Aug
dust216–120.0223%23 Aug
mirage13–80.1112%23 Aug
inferno13–80.1614%18 Aug
cache10–130.036%8 Aug
nuke8–13-0.0114%22 Jun
ancient9–13-0.0515%22 Jun
inferno6–130.0022%18 Jun
nuke10–130.0114%17 Jun
dust213–4-0.038%17 Jun
nuke13–80.069%17 Jun
inferno13–16-0.0610%17 Jun
mirage5–13-0.0326%17 Jun
dust216–14-0.0011%16 Jun
nuke6–13-0.0615%16 Jun
dust29–130.035%16 Jun
dust213–9-0.0317%16 Jun
dust213–70.0724%16 Jun
dust213–80.0410%16 Jun
overpass7–130.0325%16 Jun
nuke13–110.0213%16 Jun
dust210–130.0314%15 Jun
anubis13–70.0819%15 Jun
inferno2–13-0.047%15 Jun
ancient14–160.0015%15 Jun
mirage13–10-0.0624%14 Jun
inferno8–130.0117%10 Jun
ancient13–70.0023%9 Jun
ancient13–90.0011%9 Jun
inferno6–130.0216%9 Jun
nuke4–13-0.0814%9 Jun
dust213–90.0522%9 Jun
dust213–20.0727%9 Jun
mirage6–13-0.029%9 Jun
mirage13–8-0.0112%9 Jun
anubis9–13-0.0516%8 Jun
mirage13–90.0610%8 Jun
dust27–130.0221%8 Jun
cache2–13-0.036%7 Jun
overpass8–13-0.046%24 May
dust25–130.077%8 Mar
dust26–13-0.220%15 Feb
ancient13–5-0.0012%9 Jan
nuke2–13-0.0320%28 Dec
mirage13–6-0.0210%28 Dec
ancient16–140.008%28 Dec
dust26–13-0.0223%27 Dec
mirage13–11-0.0317%27 Dec
mirage5–100.0210%2 Nov
nuke15–150.0422%2 Nov
train9–13-0.0520%2 Nov
ancient13–90.0019%2 Nov
inferno9–13-0.0421%2 Nov
mirage2–13-0.0611%28 Oct
dust213–90.1125%26 Oct
office13–9-0.0228%26 Oct
mirage6–10-0.100%23 Oct
nuke5–0-0.0411%23 Oct
inferno4–8-0.0412%22 Oct
dust25–13-0.0328%21 Oct
inferno13–90.0329%20 Oct
ancient13–11-0.0125%19 Oct
mirage1–6-0.070%19 Oct
mirage15–15-0.0510%19 Oct
ancient4–9-0.0513%19 Oct
mirage12–120.0518%18 Oct
dust25–13-0.0424%18 Oct
mirage13–50.0433%18 Oct
inferno5–13-0.0018%18 Oct
inferno9–60.0416%17 Oct
mirage13–40.1611%17 Oct
mirage13–60.0532%16 Oct
inferno8–80.1130%16 Oct
nuke2–130.0817%14 Oct
inferno12–12-0.0114%12 Oct
ancient9–130.0416%12 Oct
dust213–10-0.0113%12 Oct
mirage2–130.0431%12 Oct
train15–15-0.0514%1 Oct
inferno1–7-0.170%1 Oct
overpass13–10-0.0523%30 Sept
ancient13–70.0620%30 Sept
overpass2–4-0.0313%30 Aug
anubis13–110.0515%24 Aug
dust24–13-0.0422%19 Aug
train7–13-0.0421%19 Aug

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 →