NEWThe Spotlight · player features
The most underrated players across the globe, each rating far above the roster around him, read through the CAR Index and a season of watching every league. Awards follow records, the data shows where they are missing.
Read The Purgatory Files →Each one's CAR against the average of the four teammates around him. Not one of these rosters rates as high as the man on it.
One top laner, one mid, two ADCs: four seasons better than the rosters around them. Every claim corroborated against the CAR Index, names inside.
Read essayThe Dissection
Fifteen days, 71 games, 11 teams. Every chart on this page is built from MSI games alone: no domestic form carried in, no reputations, no benefit of the doubt.
Each radar is the player's shape against the rest of his role at MSI: the outer ring is two standard deviations above the field, the middle ring is the field's average. The axes are the components of that role's CAR formula, so this is the same model the index runs, pointed at fifteen days of games instead of a season.
Loading the MSI dataset…
Ranked by MSI-only CAR, minimum 4 games: the top ten, then the bottom five. A rank here is a claim about these fifteen days, nothing more, and nothing less. The middle of the pack lives in the CSV below.
Built from the Oracle's Elixir per-game refresh, MSI slice. Download the computed dataset or the raw per-game rows.
JTE is an independent analytics publication for professional League of Legends, built around the CAR Index, a composite, replacement-relative score of player value. The numbers find what conventional coverage misses; the writing explains why it happened.
Every gap between the record and a player's established level is a built-in narrative: expectation versus reality. Arguments are built to hold up, not to be agreeable. 0% AI-written content.
Narrated conclusions from the CAR Index, data-armed analysis of pro League.
Contribution Above Replacement, league-relative player evaluation across professional LoL. Every row is a portal: open a player for their skill estimate, components, and the stories the numbers surface.
CAR is a composite performance score measuring a player's output against a freely replaceable player at the same position, on an artificial scale, not a wins total, and not WAR. Figures are not cross-league comparable. What is CAR? →
Positioning lenses on the CAR Index. The outliers are the story, hover any point, click it to open the player.
League-relative figures, points are not cross-comparable between regions or years.
A composite, replacement-relative score of individual player value. Rigorous on the logic, deliberately honest about what it can't see. Read this before you argue with a number.
Every league has a freely available floor: the players a team could sign tomorrow with no real cost. Call that replacement level, concretely, the 25th percentile of qualifying players at each position. CAR is how far a player's output rises above that floor, a composite score on an artificial scale, not a count of wins. A replacement-level player scores 0. The rest is what you actually bought.
Raw stats reward players on winning teams and punish players on losing ones. So CAR is built almost entirely from numbers that cannot carry team level: a player's share of his own team's farm, gold or kills; his damage per unit of gold spent; his share of the damage against his share of the dying; and his lane result measured against the opponent standing in front of him. A share cannot rise just because the team is winning, and a duel with the enemy laner is a duel whoever else is on the map.
Where a share is shaped by circumstance, CAR scores it against expectation instead of deleting it. A top laner on a team that barely touches towers will post a huge slice of a tiny pie; one on a dominant team is buried in a big denominator. So tower pressure is credited as output above what an average player would post with those same teammates — the environment becomes the baseline, not the signal. And a stat only earns a place in a formula if it moves with a player's own good and bad stretches: habits that merely differ from player to player — however reliably — describe style, and stay out of the score.
Every role is built separately, because the same statistic means different things in different seats. Gold difference at ten minutes is close to a clean duel result in the top lane and nearly meaningless in the bot lane, where two players and a jungler decide it.
The same logic is applied to the champion itself. Some champions inflate the box score through their kit alone, not through better play, so CAR treats every champion as a park factor and strips that inflation out before anything else is computed. What remains is a champion-neutral estimate of the player, and it is worth seeing how that is done.
A support on Nami and a support on Pyke are not playing the same statistical game. One of them places wards because that is the job the kit hands him; the other roams and gets credited for it. Ivern will never post damage numbers, Zyra cannot help posting them. Senna gives up early gold by design. None of that is a judgement about the player, and all of it lands in the box score, so it is measured and removed before a single component of CAR is computed.
The estimate is made on the champions, not on the players. For every raw statistic the formulas use — damage per minute, gold and damage share, kill participation, deaths, wards, gold and CS difference in lane, tower damage — the model fits a per-champion effect from every game in the tracked leagues: how much does this champion move this number, on its own? Each effect is fitted inside its own role, region and season, because a champion is a different tool in the top lane than in the bot lane, and a different tool in one patch cycle than the next. Thin cells are pulled toward zero: a champion picked six times does not earn a strong correction, it earns a cautious one. Effects are refitted each split and carried forward with the neighbouring splits, so a champion that drifts with the patch drifts in the model too.
Then it is subtracted, player by player, through the pool he actually played. A player's correction is the average of his champions' effects across his own games, weighted exactly the way the statistic itself is built — by minutes for a per-minute rate, by his team's kills for a kill share, by games for a lane differential. Play ten games of the champion and you carry ten games of its effect; play it once, and once. That subtraction happens on the raw season totals, before damage efficiency, damage-per-death, kill participation over expectation and the vision terms are derived, so every downstream number is built on champion-neutral inputs rather than patched up afterwards.
The honest limits. A champion's effect is fitted from everyone who played it, which includes the player being corrected, so a player who is effectively the only one on a champion is partly measured against himself. In practice that is rare, and it concentrates in tiny samples: across a league season, about one game in a hundred sits in a champion cell that a single player owns outright. And neutralization deliberately does not credit the pick. Choosing the champion that inflates your numbers is a real skill; it is not the skill CAR is trying to measure.
CAR is built from what shows up in the data. A great deal of competitive League does not:
So system-oriented junglers and facilitating supports can read lower than their real contribution. CAR is a strong prior, not a verdict. The number opens the argument; the film closes it.
Replacement level is recomputed inside each league and split, and cross-region samples are reset. A +30 in the LCK and a +30 in a development league are not the same achievement; they're measured against different floors. CAR ranks players within a competitive environment, never across them.
The model produces two genuinely different scores, and the site shows both because the gap between them is the story.
A rookie with a monster split posts a high raw CAR but a shrunk pCAR, the model doesn't trust the sample yet. That tension is the engine behind every "is he actually this good" argument. See it on the record-vs-estimate chart →
JTE is an independent analytics publication for professional League of Legends. It is built around the CAR Index, Contribution Above Replacement, a composite, replacement-relative score of individual player value, and the stories that the index surfaces but conventional coverage misses.
The approach is empirical: a forecaster minimizes surprise, but a story maximizes it. The same model devices, read for their residuals and gaps, become narrative engines, the player whose record outruns his established level, the roster beating its own pieces, the floor quietly rising across a region.
Pieces run long when the argument demands it. Data is used when it's honest, and always with its limits stated. The goal is analysis the scene deserves but rarely produces for itself.
| Author | JTE, pseudonymous |
| Coverage | Professional League of Legends, player value (CAR / pCAR), team performance, positioning & trajectory analysis |
| Format | The interactive CAR Index · positioning charts · data-armed long-form stories · short takes on Twitter / X |
| Contact | Twitter / X, DMs open |