From the Third Cushion to the Scoreboard: Tempo and Hidden Data in Vietnamese Billiards' Annual Season

In the opening 3-cushion final of the 2026 annual season in Binh Duong, the winner averaged only 1.72 points per turn — lower than the loser. The crowd roared when he finished with a difficult three-cushion shot, but the data sheet I kept throughout the match showed something else entirely: 58% of the opponent's turns were held below two points, and in the final fifteen turns, the rate of allowing the opponent to score fell to just 21%. The winner did not score more points. He made it harder for his opponent to score.

That is the moment I always search for when I sit down with the numbers after the arena lights have gone out. I am the one who tracks the numbers no one bothers to count, and in billiards, that is an entire world waiting to be explored. I was born in the Philippines, I work as a data consultant for a football club in Vietnam, but the billiards table is where I learned the most about rhythm. Twenty-three years of snooker commentary for VTC taught me that a beautiful shot means nothing without context. And context, in billiards, often lies in the turns the audience does not remember.

Before believing a number, I ask where it came from. The same way I watch a player before passing judgment.

This article is a chain of evidence I gathered throughout the early part of the annual season: from domestic 3-cushion tournaments, regional qualifiers, to the evenings I sat alone in a billiards club in Thu Dau Mot, recording every turn in a notebook. No expensive software. Only people who believe every number will find a way.

Context: when billiards lacks its own data language

Compared with football, where xG, PPDA and distance covered have become a common language, billiards is still at an early stage of data. In Europe, major snooker tournaments have begun recording time per shot, long-pot success rate, and safety success rate. But in Vietnam, most tournaments still stop at recording the final score and the number of turns. That is like recording only the score of a football match without recording who ran how much, who passed how much.

In the first three months of this annual season, I recorded detailed data for 47 3-cushion matches and 29 9-ball pool matches at clubs in Binh Duong, Ho Chi Minh City and Dong Nai. I had no automatic tracking devices. I sat in the third row, close enough to hear the ball strike the cushion, far enough not to be swept up by emotion. For each turn, I recorded four things: points scored, number of cushions struck, time taken, and the outcome of the opponent's next turn.

The fourth metric is the one I care about most. I call it the "opponent scoring rate" — that is, after player A's turn, how many points opponent B scores in the immediately following turn. This is a metric I learned from PPDA in football: how a team allows the opponent to pass reflects how they defend. In billiards, how a player allows the opponent to score reflects the quality of the "unattractive" turns — the turns the audience does not remember, but which decide the match.

The 2026 World Cup taught me the most important lesson: numbers are only beautiful when they know how to stand on the side of the story. Billiards is the same. A player scoring 10 points in one turn is a beautiful number, but if that turn comes after the opponent has tired from being squeezed for twenty turns, then it is no longer a simple number — it is the result of a process.

I started recording data in Binh Duong in 2026, when I was still a data consultant for a football club. Back then I discovered my club had only 42% possession but created 18 chances from counter-attacks. Billiards has no possession, but it has something similar: control of tempo. A 3-cushion player controls tempo not by scoring a lot, but by making the opponent unable to score in their rhythm. That is the correlation I wanted to prove with data, not with feeling.

One interesting thing about billiards is that it allows precise measurement down to each turn — something football does not have. Football has 90 continuous minutes, hard to separate. Billiards has discrete, clear units: each turn is a unit. That makes billiards an ideal environment for testing hypotheses about rhythm that I once experimented with in football. If a low PPDA shows a team defending deep, then a low opponent scoring rate shows a billiards player controlling the game well.

Core: a chain of evidence from 76 matches

When I aggregated data from 76 matches, a clear pattern emerged. Among the 47 3-cushion matches, players averaging below 2.0 points per turn but with an opponent scoring rate below 30% won 68% of their matches. Players averaging above 2.5 points per turn but with an opponent scoring rate above 45% won only 52% of their matches.

Average score is not the decisive metric in billiards; the decisive metric is the ability to control the opponent's turns.

This is something I had long suspected but lacked enough data to confirm. In snooker, people often praise big breaks — scoring runs of 100, 120, 147. But in 23 years of snooker commentary, I realized that big breaks often come after the opponent has made a mistake. And that mistake often comes from pressure created by the previous turns — safety turns, shots that push the ball into difficult positions. The audience remembers the 147 break, but not the ten safety turns that led to it.

In 3-cushion billiards, I found something similar. The best players are not those with the highest average score, but those who make the opponent score the least. In my data, there was a young player in Dong Nai averaging only 1.68 points per turn but with an opponent scoring rate of just 24% — the lowest in the entire sample. He did not win with beautiful cushion shots. He won by placing the ball in positions that forced the opponent into difficult shots.

This kind of measurement requires patience. I had to sit through the entire match, record every turn, and cross-reference with the next turn. No software does this for you. But when I plotted the scatter graph of the 47 matches, the correlation emerged clearly: the horizontal axis was average score per turn, the vertical axis was opponent scoring rate, and the colour represented win or loss. The winning points clustered in the lower left corner — average score not high, but opponent scoring rate very low.

On the 9-ball pool side, I found a different pattern. Across 29 matches, the win rate barely correlated with successful potting of the 9-ball, but correlated with the number of turns in which the player left the opponent without a direct shot — I call these "isolation turns". An isolation turn is one where, after the player finishes, the opponent has no direct shot at the target ball, forcing them into safety or a risky shot. Players with an isolation turn rate above 40% won 71% of their matches, regardless of how beautiful their technique was.

In 9-ball pool, victory belongs to the player who creates turns where the opponent has no choice — not the player with the most beautiful shot.

I linked this to my observation about VAR in football. VAR review times that are too long are tearing apart the rhythm of the match; two minutes of waiting is enough to cool down a goal. In billiards, there are also "waiting gaps" that cool the rhythm: long safety exchanges, turns where the audience sits in silence. But unlike VAR, these gaps are part of the match — they do not break the rhythm, they create it. That is what I want to say when I write about rhythm: rhythm is not only the scoring moments, but also the silences between them.

The empty arena of 2026, I heard clearly the sound of the ball rolling and the sound of my note sheet falling onto the stadium seat. The days without spectators at billiards clubs in Binh Duong taught me that the sound of the crowd is not just noise — it is part of the data. When the arena falls silent, players tend to choose safer shots. In my data for the 2026 period, safety success rate rose 14% compared with the previous period, but risky shot success rate fell 22%. The environment changed, and the style of play changed with it.

That is why I always compare data before and after the pandemic when analysing any sport. In 2026, analysing 500 European football matches, I found home teams won only 32% of matches without spectators, down from 45% the previous season. In billiards, home advantage does not come from a loud crowd, but from the player's familiarity with the table's cushions — cushion speed, ball bounce. That is a physical form of "home advantage", not a psychological one. And it does not disappear when the arena is empty.

In my 3-cushion data, players competing at a familiar club averaged 0.31 more points per turn than when competing at an unfamiliar club. The number is small, but in a match where the average per turn is only about 2.0 points, 0.31 points is a significant gap. It is like a football team playing on home turf they know well — it does not decide the match, but it creates a slight cumulative advantage over many turns.

Another finding caught my attention: time per turn. In my data, players averaging under 25 seconds per turn had a higher opponent scoring rate than players averaging over 35 seconds. This seems counter-intuitive — many people think fast play is good play. But the data shows fast play often comes with placing the ball in worse positions, creating opportunities for the opponent. In snooker, I once watched fast players score a lot but lose long matches because they gave the opponent too many chances.

Time is not the enemy of billiards; time is part of the tactics — and those who understand this usually win the long matches.

I remember a match in Ho Chi Minh City early this season. A young player, let me call him H., faced a former national champion. H. played very fast, averaging 22 seconds per turn. In the first session, H. led thanks to two consecutive beautiful cushion shots. But by the third session, the former champion began stretching the time per turn, placing the ball in difficult positions, and H.'s opponent scoring rate gradually rose. The match ended in victory for the former champion, who had a lower average score but an opponent scoring rate of just 19%.

People see the goal, I see the twenty quiet minutes that led to it. In billiards, people see the beautiful cushion shot, I see the thirty turns of placing the ball in difficult positions that led to it.

Another metric I track is the "safety streak" — the number of consecutive turns in which a player does not score but still controls the game. In my data, players with an average safety streak above 4 turns had a win rate 18% higher than players with a safety streak below 2 turns. This reaffirms my argument: in billiards, the ability to control the game without scoring is no less important than the ability to score.

When I presented these numbers to a billiards coach in Binh Duong, he said: "I have known this for thirty years, but I have never seen it on paper." That is why I believe in data — not to replace intuition, but to confirm what intuition already knows but cannot prove. Binh Duong back then had no expensive software, only people who believed every number would find a way.

I extended the analysis to the physical aspect. In long tournaments, a 3-cushion player competing continuously for three hours can gradually lose accuracy. I measured accuracy by the rate of placing the ball in the desired position — I call it the "position control rate". In the first session, the average position control rate was 68%. By the final session of the third competition day, it had fallen to 54%. But one group of players maintained a rate above 62% throughout the tournament — and all of them reached the semi-finals.

Fitness in billiards is not about running a lot, but about maintaining the accuracy of a positional shot when tired — and that is a metric few people measure.

This is where I link to the observation about distance covered in football. Distance covered and sprint counts are packaged as effort metrics, but ineffective running also produces nice numbers. In billiards, the number of turns is the same. A player taking many turns does not mean they are playing well — they may simply be squeezed by the opponent. A high turn count is a neutral metric, like distance covered. What matters is how many points those turns produced and what they left for the opponent.

I return to the data from the 47 3-cushion matches. One player averaged 38 turns per match — above the average of 29. One might think he is an active, busy player. But on inspection, his opponent scoring rate was 51%, the highest in the sample. He did not play many turns because he was good — he played many because the opponent dragged him into a grinding battle, and each of his turns gave the opponent a chance. That is the kind of data that looks good but does not tell the truth.

Conversely, another player took an average of only 24 turns per match, but his opponent scoring rate was just 27%. He won 71% of his matches. Looking at the scoreboard, he seems to "play less". But in reality, he finished each turn faster and more effectively, leaving the opponent fewer chances.

Contrarian angle: correlation is not causation

There is one thing I must be careful about when presenting these numbers. Correlation is not causation. The fact that a player has a low opponent scoring rate and wins many matches does not prove that the low rate causes the wins. There may be a third factor — for example, better ability to read the table — that leads both to a low opponent scoring rate and to victory.

I once made this mistake in football analysis. In 2026, I concluded that Croatia won by running more than their opponents. But on review, I realized that running more could be a result of having less possession, not a cause of victory. Croatia ran more because they had to chase the ball. The data was correct, but the interpretation was wrong.

In billiards, I am more careful. A low opponent scoring rate may be the result of the opponent playing poorly that day, not of tactics. To eliminate this factor, I compare the same player across multiple matches. If a player maintains a low opponent scoring rate stably across many matches, then it may be a technical characteristic. If it fluctuates widely, it may be luck.

In my data, three players maintained opponent scoring rates below 30% across at least five matches. Those are the players I believe have genuine control technique, not luck.

Another contrarian point: in billiards, some players are praised for beautiful cushion shots, but the data shows they take unnecessarily high-risk shots. I measure a "risk index" by the proportion of shots that, if failed, would give the opponent a big scoring chance. Players with a risk index above 35% generally win less, regardless of how good their technique is. This is similar to football, where an inverted winger can produce beautiful plays, but if they lose the ball too often, the benefit does not compensate for the risk.

I still hold the view that inverted wingers are homogenizing football, and that traditional wingers have been wrongly erased. In billiards, there is a similar trend: young players are being taught to attack more, to take more risks, because those shots produce highlights. But my data shows that patient players with good safety play still win more in long tournaments. The attacking trend may produce beautiful moments, but not necessarily championships.

Football has its own rhythm, data has its own rhythm. It took me many years to learn to put them in the same sentence. In billiards, the rhythm of a match depends on both players. A fast player can be dragged into the slow rhythm of the opponent, and vice versa. My data shows that players who can change rhythm — fast sometimes, slow sometimes, depending on the game state — have a win rate 15% higher than players who play at only one rhythm. That is what I call "rhythm flexibility", and it is one of the hardest metrics to measure but one of the most valuable.

I remember a match in which player H., after losing the first session, completely changed his rhythm. He began stretching the time per turn, placing the ball in difficult positions, forcing the opponent to play to his rhythm. His opponent scoring rate fell from 48% in the first session to 26% in the second. He won the match. Looking at the scoreboard, people see he scored fewer points in the second session than the first, yet won. That is the power of rhythm, something the scoreboard does not record.

Every season is a string of data, but my memory is not in any model.

I remember the evenings at the billiards club in Thu Dau Mot, when only one table's light remained on and a few people stayed behind. I recorded every turn in my notebook, and sometimes looked up at a young player practising. They did not know what I was writing. They only knew that a foreign man sat in the corner, writing continuously. Once a young player came to ask what I was writing. I said I was recording his turns. He laughed and said: "Why are you recording, sir, I don't play beautifully." I replied: "You don't play beautifully, but you win." He fell silent for a moment, then turned back to the table.

That is the moment I remember most from this season. A young player realized there is another way to look at his game — not through beautiful cushion shots, but through what he leaves for the opponent. I did not tell him that I had stayed up many nights to complete this analysis sheet. I just recorded, and let the data speak.

I am the one who sits with the numbers when the arena lights have gone out — you may call it work, I call it fate.

The numbers I collect are not only for analysis. They are my way of honouring the quiet people — the players who are not praised for beautiful cushion shots, but who truly control the match. In football, they are the defensive midfielders who do not score but make the team function. In billiards, they are the safety players who do not score much but make the opponent unable to score. They are the quiet ones, and data is how they are seen.

I extended the analysis to the psychological aspect. In long matches, mental stability is the deciding factor. I measure a "stability index" by the standard deviation of points per turn. Players with low standard deviation — scoring evenly — tend to win long matches. Players with high standard deviation — scoring a lot sometimes, little at others — tend to win short matches but lose long ones. This is similar to football, where a stable team usually outlasts an erratic one over a long season.

In my data, there was one player with a very low standard deviation — he almost always scored between 1 and 3 points per turn, rarely 5 or 0. He had no truly explosive match, but he won 74% of his matches. That is the kind of player data loves — not flashy, but effective.

I link this to the change in football after the pandemic. In 2026, I realized my data had become skewed because the environment had changed. I analysed 500 matches in Europe and found home teams won only 32% of matches without spectators. I quietly sent this report to clubs in Vietnam, helping them adjust to counter-attacking play rather than proactive pressing. Seven clubs applied it, and as a result they improved their points-gaining rate by 23% in that period. The lesson is: the environment changes, data must change with it. In billiards too — when the arena falls silent, rhythm changes, and players who understand this gain an advantage.

I also noted that young players had fitness metrics up 15% due to not facing psychological pressure from the crowd, from which I created a talent list for scouts. In billiards, something similar happened: young players competing without spectators tended to take fewer risks and play more safety, leading to a lower opponent scoring rate. That may be an advantage in the future, if they keep the habit when the crowds return.

The key point I want to emphasize is: in billiards, as in football, data is not only for measuring outcomes but for understanding the process. A win is not just the final result — it is a string of turns, decisions, silences. And to understand that string, one must be patient. Must sit down when the arena lights have gone out. Must record every turn. Must believe that the truth lies in the small details others overlook.

That is why I do this work. Not for the numbers, but for the people behind them.

I remember an older player in Binh Duong who had competed for more than twenty years. He was no longer as agile as before, but still beat young players thanks to his table reading and positional play. In my data, his opponent scoring rate was 29% — one of the best figures in the sample, despite an average score per turn of only 1.9. When I asked his secret, he said: "I don't try to score a lot. I try to stop the opponent from scoring." That sentence summarizes the entire argument of this article.

I have spent many years learning to listen to players like him. They do not speak the language of data, but they understand data in their own way. My job is to translate that language into verifiable numbers, and present it in a way others can understand. That is the work of a data monk — not to impose numbers on the story, but to let numbers serve the story.

Throughout this annual season, I will continue recording data. I will continue sitting in the third row, close enough to hear the ball strike the cushion, far enough not to be swept up by emotion. I will continue measuring opponent scoring rate, safety streaks, stability index, and rhythm flexibility. And I will continue to believe that these numbers, however dry, can tell a story about the quiet people at the billiards table.

Forward-looking: signals for the next round

As the annual season enters its middle phase, I will watch three signals. First, whether players with low opponent scoring rates can maintain form as tournaments become longer and pressure greater. Second, whether fast young players adjust their rhythm when facing patient opponents. Third, whether home advantage — familiar cushion speed — still creates an edge when players compete in many different tournaments.

These signals are not predictions. They are questions I will carry into the next round, and data will answer. I do not know who will win this season. But I know the champion will be the one who understands that billiards is not only about scoring — it is about controlling the opponent's rhythm. And the one who understands this is usually the least praised.

I will be here, sitting with the numbers, when the arena lights have gone out. Because the truth of this sport does not lie in beautiful cushion shots. It lies in the turns no one bothers to count — until someone starts counting.

The question I leave for readers: if you look back at a billiards match you love, what will you count — the beautiful cushion shots, or the turns the winner left for the opponent?