Is Home Advantage Disappearing in the K League? What a 36-Match Shot Ledger Says

I opened the Busan ledger before kickoff and let every shot confess. In May 2026 the K League returned to empty stadiums; comparing 2026 and 2026 home win rates — 42.8 percent versus 31.8 percent — I refused to print a dramatic headline because the sample was only 12 rounds. Now, in the regular season, with readers watching every match, the sharper question is this: where does home advantage actually hide inside shot and position data?

Context first. In 2026, at fifteen in Busan, I began manually logging every shot of Busan IPark's 36 K League Challenge matches. That was 1,142 shots — location, body part, assist type, each in its own column. Public xG for K League 2 did not exist, so I built a simple Excel model and tested Busan's 1.24 xG against Ansan Greeners in a 0-0 draw. I believed data never lies, so I rechecked every entry twice. That ledger changed my writing habit: I lead with xG and shot maps, not scorelines, and I cite raw sample size before any claim — every number has a timestamp, and every timestamp has a witness.

Now the core. Home advantage is usually explained by crowd noise, travel fatigue and subtle refereeing bias. Inside the shot ledger the picture differs. Home teams do not take many more shots; they take better-located shots — inside the box, at better angles, at the end of longer assist chains. In my log, Busan's share of in-box shots at home sat near 58 percent, while away it fell into the high forties. Same team, similar possession, different geography of shots. That is my first counter-intuitive finding: home advantage lives in shot addresses, not shot counts.

The second layer is pressing. I read pressing as a grammar of spaces — where you squeeze and where you deliberately leave a gap tells the real plan. The Russia notebook taught me that low PPDA is not automatically aggression; sometimes it is a trap. In the K League ledger I separated defensive-action height at home and away. At home, teams start pressing in the middle third, roughly two to three metres higher, so the opponent's first pass comes under stress. Away, that line drops toward their own box and they concede circulation. A warning is essential here: is this difference a cause of home advantage or a coaching preference? Correlation is not causation — I can say the two walk together, not which one leads.

The third layer is finance and league structure. Budget gaps in K League 1 are wide, and for smaller clubs the home ground is their main capital. Look only at top teams and home advantage nearly vanishes; look at the bottom half and it is obvious. To me this is not a transfer-market rumour mill but a truth signed on the spreadsheet: big clubs buy stars and hold quality away, small clubs use familiar ground to mask squad gaps. That gap draws the line between the top and bottom of the table, and it shows most clearly mid-season.

Now the contrarian angle, where the obvious narrative stumbles. The empty-stadium sample — I still call it a sample, just a lonelier and stranger one. Announcing that home advantage died on 12 rounds of 2026 data would be wrong; ignoring it entirely would also be wrong. The ledger shows home win rates rose again once crowds returned, yet not fully to 2026 levels. Post-pandemic fixture compression, travel schedules or refereeing directives may all play a part — none is proven alone. The mistake I avoid is making attendance the sole explanation. The ledger says home benefit is mostly speed of decision and courage of position; the crowd can amplify that, not create it.

One more blind spot is rarely written about: refereeing. Whether home teams get more advantage in box-adjacent fouls is not clear in my sample; 36 matches are not large enough. Following confidence tiers, I call this a provisional signal, not a supported finding. That is the real test of data literacy — where numbers fall silent, inventing a story is not my job.

Finally, look forward. Watch two things over the next three rounds: whether the in-box shot share at home holds steady, and whether the middle-third pressing line rises. If a team's home metrics suddenly drop, external pressure — fixtures, injuries, table position — is sapping their courage of decision, and my ledger will catch it before the headline does. Patch notes are the quietest form of history, and the match ledger is their witness.