Data Gaps in Vietnamese Volleyball: The Discipline of Not Filling Blanks With Memory

On the evening of July 12, 2026, I opened the match-tracking file for a round of domestic volleyball and found every cell empty. The scoring column was blank. The first-pass column was blank. The successful-block column was blank too. The note-taker had sent exactly one line: the network at the arena went down, I could not enter anything in time. I sat still for about three minutes, hands on the keyboard, and realised I was facing the exact temptation that twelve years in this work has never made disappear: filling the gaps with memory. The memory of a beautiful rally is always readier than an honest spreadsheet. My job is to read volleyball through numbers. For twelve years I have tracked domestic and regional competitions, hand-recording every first pass and every block touch, then rebuilding the match as a table. The method is not glamorous. No sensors, no tracking cameras, no automated entry systems like the big European leagues. Most Vietnamese volleyball data still travels through paper and pen, and a person sitting in a corner of the stand, eyes locked on the net, hand ticking each box. In 2026, as a second-year student, I taught myself Python and started collecting data. I chose Liverpool as my research subject because of Klopp's gegenpressing, calculated the PPDA metric across all 380 Premier League matches of the 2026/2026 season, and wrote a two-thousand-word piece predicting Liverpool would reach the Champions League final. They reached Kyiv. The lesson I kept was not the foresight; it was the process — assumptions written down first, numbers checked second, sources stamped with dates. Moving into volleyball, I kept the same discipline. Each match, I log four metric groups: first-pass efficiency, distribution share by position, block touches, and points by set. Those four are enough to see whether a team is playing a system or playing on inspiration. They only carry value when they are recorded in full. An empty file is not a neutral file. It is a trap. My experience watching matches tells me that public data in regional competitions usually contains only the score and the roster. The workload that the main hitters of Vietnamese volleyball — names like Trần Thị Thanh Thúy or Nguyễn Thị Bích Tuyền — carry each match is the number that determines how the whole system runs. That night I had two options. I could rewrite the match from memory, sprinkle in a few plausible numbers, and file on deadline. I could also tell my editor I had no data. I chose a third path: rewatch the entire match video and record it by hand from scratch. It took nearly five hours for three sets. I paused on every rally, marking the passer's position, the quality of the ball delivered to the setter, and the distribution choice. The rebuilt table showed a very clear curve. In set one, the home team's standard first-pass rate stood at 47 percent. Set two: 39 percent. By set three it had fallen to 28 percent. What matters lies behind that number. As first-pass quality deteriorated, the setter lost the ability to run quick options. The share of high balls to the opposite position rose from 41 percent to 63 percent of all sets. Technically that is a rational choice: a bad pass goes out to the wing for the strongest arm. Tactically, it is self-handcuffing. With only one option left, the opposing block only has to read one direction. The visitors' block touches rose from 6 to 14 across two sets. Here I have to be careful with myself. A single metric always carries the power to lead me astray. Looking only at the opposite hitter's scoring rate, I would conclude she attacked poorly in set three. Looking alongside pass quality, the picture flips: her attempts soared, the quality of the ball she received fell, and the success rate inevitably fell with it. She did not attack worse. She was pushed into a harder problem. I cross-checked against a second source. The organiser's record, though missing many cells, still had the per-set scores. They matched. A record kept by a fan group watching the broadcast also matched on scoring and diverged on blocks, because they logged by feel. Two independent sources, one conclusion. That is the minimum bar before I let myself write. One more detail the table does not display. Set three lasted 34 minutes, longer than the first two combined. The home team recorded 71 digs in that set, the highest of the match. At the same time, the jump-attempt count of the two main hitters passed 60. Physical load became the variable. Not emotion, not luck. Physical load, plus a passing system that could no longer hold its structure. When the arena empties, the numbers begin to speak. There was no crowd here, but there was something similar: the noise of commentary. People said the home team lost its spirit. The table said the home team lost its passing structure, and that structure collapsed before the spirit had a chance to. The greatest enemy of the analyst is not the data gap. It is false data presented neatly. An empty cell is visible to everyone. A fabricated number sitting mid-table goes unchecked, and it will outlive the truth because it is easier to read. On the night Germany collapsed, I learned to test my own assumptions. I once believed the stronger team wins over a long sequence, and the running-distance data of German midfielders in 2026 showed me the opposite. Since then, whenever a conclusion sounds too smooth, I go looking for where the data is missing rather than looking for more evidence to support it. In volleyball, that trap wears a familiar face: the spirit story. A team loses because its spirit dropped, a team wins because of its character. Those statements are not wrong; they are simply unmeasurable. And what cannot be measured cannot be improved through a training plan. Fans are not a variable; they are a weight. They deserve an explanation that can be checked, rather than a story that sounds pleasant. What I want to say plainly: refusing to analyse is also a valid result. When the data is insufficient, the most honest answer is a gap marked clearly. Before you burn the tactics, check your data source. An analysis built on empty cells is only a guess wearing makeup. The signal I am tracking next round does not sit in the standings. It sits in the two teams' first-pass rate in the third set, in block touches when the first ball is poor, and in how the setter distributes when the quick options are gone. Those three indicators call the result better than any prediction. The season is long, the data is cold, and patience is the only measure.