How Offangle Analyzes VALORANT Replays

How Offangle analyzes a replay

Offangle currently supports ranked Competitive replays. The analyzer reconstructs the match from replay events, including player movement and vision-blocking abilities, then projects that information onto a 3D map model. Ray casts identify when an opponent is actually visible from the player’s point of view. That verified first contact becomes the reference point for timing, crosshair, shot, duel, and trade measurements.

1. Reconstruct Replay events are placed on the map with player movement and relevant visibility blockers.
2. Verify contact Visibility ray casts find when an opponent can be seen, rather than assuming every shot is comparable.
3. Explain patterns Measured events become readable metrics, comparisons, trends, and practice clues.

Scoreboard metrics

The scoreboard keeps familiar match results next to Offangle’s mechanical analysis, so you can connect what happened to why it happened.

ACS

What it measures: The combat score reported for the player in the analyzed match.
How to interpret it: Use it as a broad combat-output summary, then inspect the mechanical and teamplay sections for more actionable detail.
Direction: Higher usually means more combat impact.
Keep in mind: ACS is a match-result statistic, not an Offangle aim measurement.

K / D / A and K/D

What it measures: Kills, deaths, and assists are shown together; K/D is kills divided by deaths in dashboard trends.
How to interpret it: Pair the ratio with round context, opponents, and tradeability instead of treating it as a complete performance score.
Direction: Higher K/D is generally better.
Keep in mind: A small number of rounds can make ratios swing sharply.

ADR

What it measures: Average damage per round for the player.
How to interpret it: Higher ADR indicates more damage contributed across rounds, even when that damage did not become a kill.
Direction: Higher is generally better.
Keep in mind: ADR does not explain target selection, timing, or whether teammates converted the damage.

First kills and first deaths

What it measures: The player’s opening kills and opening deaths in the match, shown as FK–FD.
How to interpret it: Compare both sides of the opening-duel result: frequent first deaths may point to positioning or timing issues, while first kills show opening impact.
Direction: More first kills and fewer first deaths are generally favorable.
Keep in mind: Opening fights are role- and strategy-dependent, so read them alongside duel and teamplay context.

Aim metrics

Aim metrics isolate what happens from the moment an opponent can first be seen. They are designed to answer whether your crosshair, timing, and shot discipline were ready for the fight.

Aim Score

What it measures: A versioned composite score from 0 to 100 that summarizes overall aim performance.
How to interpret it: Use it as a quick directional summary, then open the component metrics to find the practice target.
Direction: Higher is better.
Keep in mind: A score can be provisional or have limited reliability; the displayed reliability and definition version matter.

Reliability and provisional status

What it measures: Reliability communicates how much usable evidence supports an Aim Score; provisional marks a score produced under a provisional definition or state.
How to interpret it: Treat a low-reliability or provisional score as a useful signal, not a precise ranking.
Direction: Higher reliability means more confidence in the summary.
Keep in mind: Reliability is not another aim skill and should not be compared like accuracy.

Crosshair placement

What it measures: The median angular distance, in degrees, between the crosshair at first contact and the enemy head at first damage.
How to interpret it: A smaller angle means the crosshair started closer to head level when the fight became actionable.
Direction: Lower is better.
Keep in mind: It is a median, so it describes the typical measured engagement rather than every peek.

Time to damage (TTD)

What it measures: The time between first contact—when the opponent becomes visible—and the player’s first damage against that opponent, shown in milliseconds.
How to interpret it: Lower TTD usually means you recognized and acted on the opening more quickly.
Direction: Lower is better.
Keep in mind: Only engagements with a verifiable first contact and measurable outcome contribute.

Time to kill (TTK)

What it measures: The time between first contact and the enemy’s death in successful measured engagements, shown in milliseconds.
How to interpret it: Lower TTK suggests faster conversion after the opponent became visible.
Direction: Lower is better.
Keep in mind: It only describes successful engagements and is affected by weapon, distance, damage, and teammate involvement.

Rifle first-shot accuracy

What it measures: The hit rate for eligible first shots from the Bulldog, Guardian, Phantom, Vandal, and Warden.
How to interpret it: It is a focused read on initial precision before a burst or spray develops.
Direction: Higher is better.
Keep in mind: It excludes non-standard rifles and is reported only when eligible shots exist.

Enemy-spotted accuracy

What it measures: Hits divided by eligible shots fired while an enemy was visible, across the analyzed weapon breakdown.
How to interpret it: Higher values indicate that more enemy-visible shots connected.
Direction: Higher is better.
Keep in mind: It is not total-bullet accuracy: shots fired while an enemy was not visible are not part of this measured population.

Movement accuracy

What it measures: The share of eligible shots without a detected movement violation: one minus movement-violation shots divided by eligible shots.
How to interpret it: Higher values indicate better shot discipline while moving or stopping for a shot.
Direction: Higher is better.
Keep in mind: This measures movement discipline, not whether the bullet hit the enemy.

Duel metrics

Duels reorganize the same evidence around a specific opponent, helping you find recurring matchups instead of hiding them inside a single average.

Opponent record

What it measures: Kills, deaths, encounter count, and an ahead/even/behind outcome for each opposing player.
How to interpret it: Use repeated encounters to identify who consistently gains the first advantage.
Direction: More kills, fewer deaths, and an ahead outcome are generally favorable.
Keep in mind: One encounter is not a stable matchup trend.

Duel timing

What it measures: Per-opponent crosshair placement, time to damage, and time to kill for measured engagements.
How to interpret it: Compare the opponent-specific values with your overall aim values to separate a general issue from a matchup issue.
Direction: Lower crosshair distance, TTD, and TTK are better.
Keep in mind: Unavailable or limited samples should not be read as a zero.

Duel gunplay and hit distribution

What it measures: Enemy-visible accuracy, movement accuracy, weapon and firing-pattern breakdowns, and hit locations for the selected opponent.
How to interpret it: Look for a weapon, range, or body-region pattern that explains why the matchup was won or lost.
Direction: Higher accuracy and movement accuracy are better; head-hit share is context-dependent.
Keep in mind: The same eligible-shot and sample-size rules apply as in the weapon view.

Weapon metrics

Weapon analysis turns a single accuracy percentage into a view of how you actually used each gun.

Eligible shots and hits

What it measures: Eligible shots are shots fired while the enemy was visible; hits are successful hits within that measured set.
How to interpret it: Always read the percentage together with its shot count. More observations make a comparison more stable.
Direction: Higher accuracy is better; a larger sample improves confidence rather than performance.
Keep in mind: Eligible shots are not total weapon usage.

Enemy-spotted and movement accuracy

What it measures: Per-weapon enemy-spotted accuracy is hits divided by eligible shots; movement accuracy is the share without movement violations.
How to interpret it: Use the pair to distinguish aim execution from firing while still moving.
Direction: Higher is better for both.
Keep in mind: A limited sample is labelled instead of being presented as a reliable benchmark.

Tap, burst, spray share, and Vandal utilization

What it measures: The percentage of eligible shots classified as taps, bursts, or sprays for supported rifles; public rank charts also show how Vandal shots are distributed across those patterns and distance bands.
How to interpret it: Compare firing choices with distance and accuracy to see whether your pattern fits the engagement.
Direction: There is no universally best mix; effectiveness depends on range and weapon.
Keep in mind: Some shots may remain unclassified and not every weapon has this breakdown.

Distance bands

What it measures: Firing-pattern usage is grouped into 0–15 m, 15–30 m, and 30+ m bands.
How to interpret it: Use the bands to decide whether your tap, burst, or spray choice changes appropriately with range.
Direction: No single distance or pattern is inherently better.
Keep in mind: A band may have too few observations for a dependable cohort comparison.

Body-hit distribution

What it measures: Successful eligible hits grouped into head, torso, arms, legs, feet, and unknown regions.
How to interpret it: Use it to spot where connected shots land and whether crosshair placement practice is reaching the target.
Direction: More head hits can be useful context, but the best distribution depends on the fight.
Keep in mind: It describes hits, not every shot fired.

Teamplay and trades

Trades measure whether a team converted the short window after a death. They describe coordination around a fight, not just individual aim.

Trade opportunities and opportunities / round

What it measures: A trade opportunity exists when a teammate can engage the killer within three seconds of a teammate’s death; opportunities / round is that count divided by analyzed rounds.
How to interpret it: More opportunities mean more moments where spacing or timing could create a trade.
Direction: Context-dependent; opportunities are chances, not successes.
Keep in mind: No opportunity is recorded when the event cannot be scored or the teammate was last alive.

Trade attempts

What it measures: An attempt is recorded when a player shoots, damages, eliminates, or makes a committed peek toward the killer within the three-second window.
How to interpret it: Trade attempt rate shows how often available opportunities became deliberate actions.
Direction: Higher attempt rate can be favorable when opportunities are genuinely playable.
Keep in mind: An attempt is not automatically successful.

Successful, unsuccessful, and failed trades

What it measures: Attempts are separated into successful conversions, unconverted attempts, and lost attempts where the attempting player died.
How to interpret it: Use the outcome split to distinguish hesitation from execution under pressure.
Direction: Higher success and lower lost or unsuccessful rates are generally favorable.
Keep in mind: The outcome is only evaluated for attempts that can be scored.

Tradeable death and traded death

What it measures: Tradeable death rate is the share of assessed deaths with a teammate opportunity; traded death rate is the share of analyzed deaths followed by a teammate elimination of the killer.
How to interpret it: Compare them to see whether available recovery windows were actually converted.
Direction: Higher traded-death rate is generally favorable; tradeable-death rate is a context measure.
Keep in mind: Unknown deaths, last-alive deaths, and unscorable active episodes are shown as coverage limits.

Heatmaps

Heatmaps add location and round-side context to your fights. On supported maps, switch between all rounds, attacker rounds, and defender rounds.

Alive time and playtime

What it measures: The amount of time the player stayed alive in each mapped region.
How to interpret it: Use it to see where you spend time and which areas are actually part of your match experience.
Direction: Neither higher nor lower is inherently better.
Keep in mind: More time in a region does not by itself mean better positioning.

Rounds, kills, and deaths

What it measures: Mapped region totals for rounds played, kills, and deaths.
How to interpret it: Use the counts to understand how much evidence supports a region’s result.
Direction: Counts are context, not a score.
Keep in mind: Small regional samples can make the next fight disproportionately important.

Regional K/D

What it measures: Kills divided by deaths for each map region, optionally filtered by round side.
How to interpret it: A region above 1.0 has more kills than deaths in the mapped sample; compare it with alive time and counts.
Direction: Higher is generally better.
Keep in mind: Regions with no kills or deaths have no meaningful K/D value.

Trends and rank benchmarks

Offangle combines match history and aggregate replay data to show whether a metric is repeating and how it compares with a rank cohort.

Latest-30-match trends

What it measures: Player dashboards show per-match trends across the latest 30 Competitive matches when data is available.
How to interpret it: Look for a direction across several matches rather than reacting to one outlier.
Direction: The desirable direction depends on the metric.
Keep in mind: Different matches can have different sample counts and metric-definition versions.

Rank-aware benchmarks

What it measures: Measured values can be compared with selected competitive-rank cohorts or all competitive players.
How to interpret it: Treat a benchmark as a reference point for practice priorities, not as a universal skill cutoff.
Direction: Compare using the metric’s own direction: lower for timing and crosshair distance, higher for accuracy.
Keep in mind: Benchmarks are drawn from Offangle submissions and may fall back to a broader cohort when the selected sample is limited.

Sample weighting and coverage

What it measures: Aggregates use the relevant engagement, match, shot, or contributing-player counts instead of treating every displayed row as equal.
How to interpret it: Check the measurement count beside a value before drawing a strong conclusion.
Direction: More evidence generally improves confidence, not the metric itself.
Keep in mind: This dataset is made from submitted replays and is not a complete or random sample of Riot’s global playerbase.

Data quality and limitations

Replay analysis is evidence-based, not a perfect account of every intention or decision. A value can be missing because the replay did not contain enough eligible evidence, an event could not be verified, or a metric does not apply to that selection.

Eligible: The event passed the conditions needed for a metric to be considered.
Measured: An eligible event produced a value that could be included in an aggregate.
Censored: The replay ended or the event changed before the requested outcome could be observed.
Ambiguous: The replay contained conflicting or insufficient evidence to assign the event confidently.
Unavailable: There is no usable value for the selected match, player, weapon, cohort, or sample.
Middle 50%: The interquartile range from the 25th percentile to the 75th percentile, used to show the middle half of observations.
Reliability: A confidence signal for how much usable evidence supports a summary such as Aim Score.
Definition version: The version of the metric or scoring definition used to produce a result; versions can change how future results are calculated.

Public rank benchmarks are aggregate observations from replays submitted to Offangle. They are not statistics for Riot’s complete global playerbase and may not represent every region, role, rank, or play style. Use them as directional context, not a promise of what a player should score.

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Upload a supported replay to see these measurements in context, or browse the public dataset to understand how rank-level trends are aggregated.

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VALORANT replay analysis, explained.