Billiards in the Data Drought: When an Empty Analysis Table Exposes a Hole in the Whole Industry

Billiards in the Data Drought: When an Empty Analysis Table Exposes a Hole in the Whole Industry

In October 2026, in a small flat in east London, I sat in front of my screen at two in the morning and watched something that made me stop for a very long time. The data-extraction pipeline I had painstakingly built for a professional billiards event — expected to return thousands of rows on shot selection, turn duration, pot success rate and a heat map of ball positions on the table — returned exactly one line: "billiards." No tournament name. No player name. No score. No specific discipline. Just a bare domain label sitting there, exactly like a white cue ball coming to rest in the middle of the table after every coloured ball has vanished from the cloth.

I call that phenomenon a "data vacuum." It is not a mere technical glitch. It is a mirror reflecting a much larger problem across the global billiards industry. While football has built a data ecosystem so sophisticated that a single pass can be priced by its percentage chance of leading to a goal, billiards — a sport with more than a century of history — is still wrestling with the most basic question of all: which discipline are we even talking about?

An umbrella sheltering too many things beneath it

The word "billiards," in English as well as in Vietnamese, is a giant umbrella sheltering at least five completely different disciplines in terms of rules, technique, tournament systems and even commercial foundations. There is snooker (English-style pocket billiards), American 9-ball and 8-ball, Chinese 8-ball (played on a larger table with larger balls), carom (pocketless billiards, including three-cushion and straight rail) and Russian pyramid. Each has its own governing body, its own ranking system, its own scoring logic and its own distinct fan community.

This confusion is not merely academic. It is the root of every data problem my colleagues and I encounter when we try to analyse this sport seriously. When an information-extraction system receives an article about "billiards" with no cue words — no tournament name, no table description, no rule terminology — it cannot select the correct technical vocabulary set. With snooker, we talk about break-building, safety play, and snookers. With 9-ball, we talk about break shots, push-outs and jump shots. With Chinese 8-ball, we talk about group assignment, break-and-run and the deciding black. Three vocabularies, three logics, never to be mixed.

This is exactly what I always stress in internal training sessions: the first step of any billiards analysis is to identify the discipline, because the rules, technique and commercial ecosystem of each discipline differ fundamentally and must never be conflated.

The data map of five disciplines

Let us start with snooker, the discipline with the best data infrastructure in the billiards family. The governing body is the WPBSA (World Professional Billiards and Snooker Association), while the tour is run by WST (World Snooker Tour). The trio of events known as the Triple Crown — the World Championship at the Crucible Theatre in Sheffield, the UK Championship and the Masters — forms the backbone of the calendar. The two-year rolling ranking system is updated after every event, and this is where the data genuinely has depth.

Core snooker metrics include century breaks (visits scoring 100 or more), the frequency of 50-plus breaks, pot success rate, the number of decisive pots under pressure and the win rate in open visits. These figures are recorded by platforms such as CueTracker and snooker.org, which store data going back decades. Ronnie O'Sullivan, with seven world titles, holds the career record for century breaks and maximum 147s. Stephen Hendry also has seven world titles, while Steve Davis has six. The next generation includes Judd Trump, Mark Selby with four titles, John Higgins with four, and Mark Williams with three.

But even snooker, the most "data-rich" discipline, still lacks a metric equivalent to football's xG. There is no standardised measure of the quality of a safety shot, the difficulty of the position left behind, or the expected value of a visit based on the cue ball's position relative to the object ball. Every high-quality analysis still has to be done manually, match by match.

Moving to American pool, the picture is far blurrier. The WPA (World Pool-Billiard Association) is the nominal governing body, but the biggest events are staged by Matchroom Pool — such as the Mosconi Cup, a team event between Europe and the United States. Stars like Jayson Shaw, Joshua Filler, Albin Ouschan and Shane Van Boening are best known through televised events, but detailed data on break-and-run rates, pot success in difficult situations or season-by-season performance is scattered everywhere, with no common standard.

Chinese 8-ball is even younger in data terms. Largely governed by the CBSA (Chinese Billiards and Snooker Association), the discipline has its own world championship and a vibrant commercial tournament circuit in China. Cueists such as Zheng Yubo and Gareth Potts stand out, but publicly accessible databases barely exist in any automatically retrievable form.

Carom, with the UMB (Union Mondiale de Billard) as its governing body, has a long tradition in Europe and legendary cueists such as Dick Jaspers, Torbjörn Blomdahl and Frédéric Caudron. But metrics such as average per turn or success rate by position are recorded only fragmentarily in tournament scoreboards.

Why a vacuum matters so much

Based on my years of watching matches and handling billiards data, I have come to realise that a data vacuum is not harmless silence; it is a signal that a sport has not yet defined itself. The ambiguity of discipline in an information-extraction system is not the algorithm's fault — it is an honest reflection of a reality in which even people inside the industry routinely lump snooker, 9-ball and Chinese 8-ball together under one name.

Imagine the same happening to football. If an analytics system could not distinguish eleven-a-side football from futsal or beach soccer, then any conclusion drawn from it would be meaningless. We cannot apply eleven-a-side xG to futsal and then declare some team "inefficient." Yet in billiards, this confusion happens daily.

A concrete example: average pot success in snooker at professional level is far higher than in 9-ball, not because snooker cueists are better, but because the table structure and pocket size are entirely different. Comparing those two numbers directly without stating the discipline is a basic statistical error. I have seen "greatest billiards players of all time" lists that mix O'Sullivan with Efren Reyes and Van Boening without a single note about the discipline difference. That is the kind of comparison any serious data analyst must refuse.

No standardisation, a whole generation of analysis missing

The data vacuum in billiards is not only an academic matter. It has direct consequences for the sport's development. When there is no standardised data, sponsors have no basis on which to price their investment. When there are no consistent performance metrics, fans have no tool to understand why a cueist wins or loses beyond a raw scoreline. And when there is no shared data language, young cueists have no clear development path based on their specific weaknesses.

Compare this with football, where every major league has professional data providers recording every pass, every duel and every square metre defended. That investment did not appear by accident. It came from a strategic decision: to turn football into a measurable sport, so that it could then be sold more widely, broadcast further and attract a new generation of fans who grew up alongside the numbers.

Billiards needs a similar decision. The good news is that part of the infrastructure already exists. In snooker, century-break and 147 data have been fully recorded for decades. What remains is to standardise it, to add contextual metrics such as cue-ball position at the start of a visit, the difficulty of the position left behind, and success rates under high pressure — all of which can be extracted from video using modern computer-vision technology.

The blind spot of trusting the scoreboard

Here is the most counter-intuitive part. Many people in billiards believe the scoreboard already tells the whole story: whoever scores more wins, and that is that. But the scoreboard is only the final outcome, not the process. A cueist can win 10-8 because an opponent made mistakes in decisive visits, while the loser actually held a higher consistency index throughout the match. If we only look at the scoreboard, we will draw the wrong conclusion about who truly played better.

In football, we learned this lesson long ago: a team can have 70% possession and fire 20 shots yet still lose 0-1. The xG metric was born to expose the gap between outcome and process. Billiards needs an equivalent metric — something that measures the quality of the chances a cueist creates and the quality of the chances they leave for opponents.

I once spent several seasons cross-checking data on the top snooker cueists across long-format events. What I found was that the players who won the most titles were not necessarily those with the highest pot success rate. They were the ones with the most consistent pot success rate in high-pressure visits — specifically, visits that decided a frame or decided a match. That is an entirely different variable, and it only emerges when you take the trouble to break the data down by context.

The story of a vacuum

Back to that night in October. The empty extraction result taught me something that no full dataset had ever taught me. It forced me to admit that the billiards industry is not yet ready for the kind of analysis football mastered over a decade ago. The infrastructure is not there. The industry standard is not there. And most importantly, consensus on which disciplines need separate datasets is still far away.

But a vacuum is also an opportunity. Precisely because billiards data is so sparse, the value of the first person to build a standardisation framework will be enormous. Precisely because disciplinary ambiguity still exists, the first person to clearly separate snooker, 9-ball, Chinese 8-ball and carom into independent data systems will hold the advantage. And precisely because the scoreboard is still believed to be enough, an xG-style metric for billiards — even a rough one — will spark an entirely new debate in the community.

I do not have enough data to claim when that will happen. But I know one thing for certain: anyone entering this field first must start from the very first step my own system failed at — identifying the discipline before saying anything else.

Data limitations

This article is based on personal observation of billiards data infrastructure between 2026 and 2026. The publicly available sample size for each discipline is uneven: snooker has the deepest historical data, while carom, Chinese 8-ball and American pool lack publicly verifiable datasets. I make no quantitative claims about the performance of any specific cueist, because that would require standardised shot-by-shot data that does not currently exist. All observations about the data vacuum describe the present state, not a long-term forecast.

A forward-looking reflection

A data vacuum is not a full stop. It is an unanswered question, and the billiards industry has enough raw material to begin writing the answer. Match footage already exists. The rules are clear. The players are famous. What is missing is only the will to invest in measurement infrastructure. When football began its data journey in the early 2010s, nobody imagined a metric like xG would become the shared language of millions of fans. Billiards can take a similar path — if someone is patient enough to start from a single white cue ball resting in the middle of the table.