John Rod — CS2 Stats

US76561198239878430[U:1:279612702]Steam profile ↗✓ No bans

1,252Tracked matches70%Win rate2023Tracked since

CSDB Rating3.6 LearningPositional Player

CSDB Leaderboard#256734 of 260019 tracked

Ladder ranks via Leetify

Performance scores

Aim31

Positioning41

Utility17

0–100 skill scores via Leetify.

Recent form

STEADY57–35–8Last 10057%Win rateWWLWTTWLLL

Last 10 vs previous 10: −50pp win rate · −0.01 avg rating · −4.8pp headshot accuracy · +29ms reaction

Win rate down 50pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

3–1–1 · 60% win rate
Avg rating -0.00
Avg headshot accuracy 13%
Avg reaction 639ms

Last 10

4–4–2 · 40% win rate
Avg rating -0.04
Avg headshot accuracy 12%
Avg reaction 609ms

Last 20

13–5–2 · 65% win rate
Avg rating -0.03
Avg headshot accuracy 15%
Avg reaction 594ms

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 (+1.8 against its own average).

Aim3.1

Utility1.7

Positioning4.1

Opening Duels0.9

Clutch2.6

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

Plays most like m0NESY 78% playstyle similarity

Most alike: positioning profile, utility contribution.

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

Areas to improve

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

Aim3.1

Positioning4.1

Utility1.7

Mechanics5.5

Opening Duels2.1

Win Impact10.0

Composite 3.6/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.04−0.01

first ⅓ avg -0.02 → last ⅓ avg -0.04

Reaction time611ms−26ms

first ⅓ avg 638ms → last ⅓ avg 611ms

Headshot accuracy15.3%+4.0%

first ⅓ avg 11.3% → last ⅓ avg 15.3%

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

0.14Best match rating · 13–4 · nuke, 20 Sept →

42%Best headshot accuracy · 13–3 · fachwerk, 11 Oct →

422msFastest reaction time · 10–13 · inferno, 7 Sept →

13–1Biggest win · nuke, 8 Oct →

Across the last 100 tracked matches.

Highlights

8Longest win streak

W2Current streak

4–1In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 68% over 62cacheWeakest map · 31% over 13

Map	Grade	Played	Record	Win rate	Avg rating
nuke	S	62	42–20	68%	-0.02
cache	D	13	4–9	31%	-0.02
vertigo	—	4	0–4	0%	-0.04
train	—	4	2–2	50%	-0.01
rush_001	—	4	2–2	50%	-0.08
shelter	—	3	2–1	67%	-0.02
ancient	—	3	1–2	33%	-0.06
mirage	—	2	1–1	50%	-0.06
fachwerk	—	1	1–0	100%	-0.07
anubis	—	1	0–1	0%	-0.03
office	—	1	1–0	100%	-0.07
inferno	—	1	0–1	0%	-0.07
dust2	—	1	1–0	100%	0.00

Across the last 100 tracked matches.

Faceit stats

Combat

15Matches

27%Win rate

0.61Avg K/D

58.1ADR

30%Headshot %

Clutches & streaks

33%1v1 clutch win

25%1v2 clutch win

1Longest win streak

Recent Faceit resultsWLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	5	40%	0.76	13.6
Ancient	3	33%	0.36	5.3
Nuke	2	0%	0.42	8.0
Mirage	2	0%	0.48	8.0
Anubis	1	0%	1.06	19.0
Inferno	1	100%	1.36	15.0
Cache	1	0%	0.07	1.0

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.

14.8%Headshot accuracy

29.5%Accuracy (enemy spotted)

36.3%Spray accuracy

74.8%Counter-strafing

16.3°Preaim

605msReaction time

42.2%T opening success

34.6%CT opening success

0.20Enemies flashed / flash

3.9%Flash assists

5.89HE damage / grenade

0.89Flashes / 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.

Advanced Mechanics
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 16.3273° — above the 12° mark we flag
Aim Training →
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 14.7648% — below the 15% mark we flag
Aim Training →
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 0.2009 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Cache

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

31% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–7	0.01	13%	4 Nov →
cache	13–8	-0.02	14%	1 Nov →
nuke	5–13	-0.01	11%	1 Nov →
nuke	13–3	0.03	12%	1 Nov →
cache	12–12	-0.03	15%	30 Oct →
nuke	12–12	-0.06	15%	30 Oct →
nuke	9–0	-0.04	13%	30 Oct →
nuke	9–13	-0.09	7%	20 Oct →
mirage	4–13	-0.09	15%	20 Oct →
vertigo	10–13	-0.06	9%	19 Oct →
nuke	13–3	-0.03	10%	19 Oct →
nuke	13–6	-0.02	9%	19 Oct →
nuke	13–9	-0.05	14%	18 Oct →
nuke	13–7	0.01	20%	18 Oct →
nuke	13–4	-0.04	18%	18 Oct →
nuke	7–13	0.01	19%	15 Oct →
nuke	13–8	-0.06	21%	15 Oct →
nuke	13–11	-0.04	12%	14 Oct →
fachwerk	13–3	-0.07	42%	11 Oct →
shelter	13–5	-0.02	6%	11 Oct →
train	10–13	-0.03	20%	9 Oct →
train	13–9	0.01	23%	9 Oct →
shelter	12–12	-0.05	14%	9 Oct →
nuke	13–3	-0.04	2%	9 Oct →
nuke	10–13	-0.07	13%	8 Oct →
nuke	13–1	0.03	5%	8 Oct →
rush_001	8–6	0.01	24%	8 Oct →
rush_001	8–6	-0.14	25%	3 Oct →
rush_001	3–7	-0.14	13%	1 Oct →
rush_001	0–4	-0.04	30%	1 Oct →
nuke	13–4	-0.08	8%	1 Oct →
nuke	13–3	-0.04	23%	29 Sept →
ancient	13–10	-0.02	14%	27 Sept →
train	9–13	0.02	26%	27 Sept →
nuke	13–2	-0.06	21%	25 Sept →
nuke	13–6	-0.01	15%	25 Sept →
cache	13–4	0.07	19%	25 Sept →
nuke	13–2	0.03	13%	25 Sept →
nuke	10–13	0.03	17%	23 Sept →
anubis	9–13	-0.03	10%	22 Sept →
cache	13–8	-0.00	16%	22 Sept →
vertigo	9–13	-0.04	12%	22 Sept →
mirage	13–2	-0.03	4%	22 Sept →
cache	6–13	-0.08	11%	22 Sept →
cache	6–13	-0.08	14%	22 Sept →
vertigo	3–13	-0.01	13%	22 Sept →
nuke	5–12	-0.06	21%	21 Sept →
nuke	13–6	-0.04	18%	21 Sept →
nuke	8–13	-0.07	12%	21 Sept →
nuke	13–4	0.14	26%	20 Sept →
nuke	10–13	-0.11	8%	19 Sept →
nuke	12–12	0.01	17%	18 Sept →
nuke	13–8	-0.05	12%	18 Sept →
nuke	5–13	-0.06	14%	18 Sept →
shelter	13–9	0.00	12%	18 Sept →
nuke	13–10	0.01	11%	18 Sept →
vertigo	3–13	-0.07	12%	17 Sept →
cache	1–13	-0.03	19%	17 Sept →
nuke	5–13	-0.04	12%	17 Sept →
nuke	13–5	0.03	13%	17 Sept →
nuke	13–8	0.04	13%	17 Sept →
nuke	13–8	0.02	7%	16 Sept →
nuke	13–5	-0.12	11%	15 Sept →
nuke	13–10	-0.07	12%	15 Sept →
nuke	3–11	-0.03	9%	13 Sept →
cache	4–13	-0.03	11%	13 Sept →
cache	7–13	-0.04	6%	13 Sept →
nuke	4–13	-0.08	10%	13 Sept →
ancient	9–13	-0.04	11%	12 Sept →
cache	12–12	-0.05	14%	12 Sept →
nuke	13–2	0.07	19%	12 Sept →
cache	10–13	0.01	11%	11 Sept →
cache	3–13	-0.04	13%	11 Sept →
nuke	5–13	-0.02	11%	11 Sept →
office	11–2	-0.07	25%	8 Sept →
train	13–6	-0.05	11%	7 Sept →
inferno	10–13	-0.07	13%	7 Sept →
nuke	12–12	0.01	16%	5 Sept →
nuke	13–3	0.05	9%	5 Sept →
nuke	12–12	0.05	11%	4 Sept →
nuke	13–6	-0.04	13%	4 Sept →
nuke	13–4	-0.08	20%	4 Sept →
nuke	13–5	-0.01	23%	4 Sept →
nuke	13–5	0.04	11%	3 Sept →
nuke	12–12	-0.08	14%	3 Sept →
cache	13–2	0.02	12%	3 Sept →
nuke	13–9	-0.02	8%	2 Sept →
nuke	13–6	0.05	9%	2 Sept →
ancient	1–4	-0.13	0%	2 Sept →
nuke	13–11	-0.05	3%	28 Aug →
nuke	13–9	-0.04	12%	28 Aug →
nuke	13–1	0.04	9%	24 Aug →
nuke	13–7	-0.03	15%	22 Aug →
nuke	13–4	-0.06	3%	22 Aug →
dust2	13–9	0.00	3%	10 Aug →
nuke	13–10	-0.02	10%	8 Aug →
nuke	13–9	-0.05	2%	8 Aug →
nuke	11–13	-0.02	7%	6 Aug →
nuke	7–13	-0.00	8%	5 Aug →
nuke	10–1	-0.06	16%	27 Jul →