Billiards Is Six Separate Sports: The Unresolved Data-Identification Problem

It took me three weeks to rebuild a billiards dataset for the UK market before I realised my mistake was not in the formula. Every time I added a match, I had to ask myself a question no software would answer for me: which kind of billiards is this. A 147 break in snooker, a break-and-run in American 9-ball, and a frame of Chinese 8-ball had all been filed by my old system into a single column labelled billiards. By the time I filtered the data to find the player with the highest win rate, I got back a meaningless list, with Ronnie O'Sullivan standing next to players who had never touched the same kind of table. That was not a technical error. It was a conceptual one, and it repeats in almost every billiards analysis table I have ever read. In English, billiards is an umbrella word. Beneath it sit at least six different competition systems: snooker, American 9-ball, American 8-ball, Chinese 8-ball, three-cushion carom, and Russian pyramid. These six differ in rules, table size, number of balls, materials, and — most importantly — the economy behind them. Snooker uses a 12-foot table and 22 balls, organised around the three Triple Crown titles: the World Championship, the UK Championship, and the Masters. Its governing bodies are the WPBSA and World Snooker Tour. American 9-ball is played on a smaller table with nine balls, tied to the Mosconi Cup and the professional pool circuit. Chinese 8-ball sits between two worlds: a table as large as snooker's but with pool balls, tied to the Joy Masters and a vast Asian audience market. When these six systems are placed in the same data column, the analyst creates a dummy variable that does not exist. A snooker player's pot success rate cannot be compared with a 9-ball player's break success rate, because the probability of success depends on the table geometry and the number of balls in play. Pooling them does not make the sample larger. It makes the sample more wrong. The first step of any serious billiards analysis is discipline identification. This is not a formality. It determines everything that follows, from technical concepts and tournament systems to governing bodies and disciplinary precedents. Technically, snooker is measured by break-building — the ability to construct long scoring sequences. An elite player is judged by century-break frequency and by cue-ball control under pressure. 9-ball is measured by break quality and clearance rate within a single visit. Both are called billiards, but the two metrics cannot be converted into each other. In tournament terms, snooker is clearly tiered between the Triple Crown, ranking events, and invitationals. A Triple Crown title carries a completely different weight from an ordinary ranking title, both in prize money and in historical value. Ignore that tiering and you will count titles as you would count match wins, flattening a record into just another number. In governance, snooker sits under the WPBSA and WST; pool under the WPA; Chinese 8-ball under its own national association. That means a disciplinary case in one discipline sets no direct precedent for another. In 2026, the John Higgins betting scandal was a snooker milestone. In 2026, the wave of sanctions against Chinese players in a match-fixing case also belonged to snooker, even though the figures came from Asia. Neither says anything about 9-ball or carom. What is notable is that anti-match-fixing rules are designed separately for each discipline. The WPBSA has snooker's rulebook; the WPA has pool's; Asian associations handle matters their own way. Conduct banned in one discipline may not be clearly defined in another. For a data worker, this is a nightmare: one event, three rulebooks, three different ways of recording it. Over years of following snooker events in England, I noticed that amateur analysts tend to make the same mistake: using one discipline's data to draw conclusions about another. They look at the dominance of a group of English players and infer that billiards is an English game. That picture is true only of snooker. In 9-ball, Filipino and Taiwanese players shaped the sport long ago. In Chinese 8-ball, the domestic Chinese market is the centre. A player's journey is not an upward arrow; it is a scatter plot. Some win a world title in their twenties and then stall. Some take a whole decade to reach the peak. The Class of '75 — O'Sullivan, John Higgins, Mark Williams — is proof of a paradox: age in billiards does not follow the physical-decline curve of football, because the sport demands mental stability and geometric memory more than muscular endurance. The medal is not on the scoreboard; it is in the success rate on difficult positional shots. A player can win a match because an opponent errs, but the clearance data is what tells you how strong he really is. In value-chain terms, billiards runs along a familiar transmission path: from practice halls and clubs, through the tournament system and broadcast, to sponsorship and derivative products. A major title can lift sales of cues and tables for a few months, but that effect stays local to the relevant discipline. A media shock in snooker does not raise demand for 9-ball, and vice versa. At the story level, billiards is also fragmented. Snooker has legends tied to British television. 9-ball has players known through international tours. Chinese 8-ball has stars who are almost unknown outside Asia. When a story crosses the boundary of its discipline, it usually loses context, and readers receive a distorted picture of who is genuinely good. There is a widespread belief that pooling data makes conclusions firmer. In billiards, the opposite is true. A larger but less homogeneous sample is a worse sample. When someone declares that billiards is growing, I always ask again: which one. Snooker in England is struggling to expand beyond Europe while keeping a loyal television audience. Chinese 8-ball is growing fast in event count and prize money but has narrow international reach. 9-ball has a global community but lacks a dense enough tournament system to generate multi-year comparable data. This is where correlation is easily mistaken for causation. A player who switches from 9-ball to Chinese 8-ball and then succeeds is often read as proof that the new discipline is easier. In reality, the sample is one person, and any conclusion drawn from it does not hold. I learned to list at least two other explanations before settling on anything: transferable skill, or simply luck in a short tournament. Another risk rarely discussed is the risk of fabrication. When an analytical framework has too many empty cells, the pressure to fill them with plausible numbers is enormous. But a fabricated number is worse than an empty cell, because it creates a false sense of certainty. In my own work, I set a rule: if there is no data, write clearly that there is no data. The arena is empty of spectators, the sound of cue on ball is clearer than ever, and so is the data. Whoever solves the discipline-identification problem first will build the first truly comparable billiards dataset. The question is no longer which discipline is best, but which one can withstand being measured honestly. Data limitations: this article is based on a structural framework of the billiards industry, not on a specific match dataset. Figures on title counts, pot rates, or prize money are not given because the source input did not provide them. The sample size for any trend claim is zero, and readers should treat this as a methodological framework, not a statistical conclusion.