How Many Runs Is Home Advantage? Pricing the Regular Season From the Ledger

Over the last three matches, this side's dot-ball percentage in the powerplay has climbed from 38 to 52. The scoreboard never registered it, because two of those three games ended with totals above 180 — the runs arrived between overs 16 and 20, where nobody audits dot balls. Put the two numbers side by side in the ledger and the picture inverts: the coin was spent early, the payout came late. The bowling unit did not change between games. The toss did, and so did the dew.

I watched that exact pattern from the press box in Bengaluru on an April evening. The home side chased 187 and won it with two sixes in the last over. The senior colleague beside me typed the words "impregnable fortress" before the players had left the field. My notebook had the pitch effect at roughly nine runs, the dew effect at another six. The crowd got five. A fortress is three separate objects, and only one of them deserves the phrase home advantage. When the market bills all three under one name, it misprices the asset.

What the regular season actually is

A franchise T20 regular season is a strange market. Each team plays fourteen to sixteen games, seven or eight of them at home. Seven games is seven observations — statistically almost nothing — yet those seven games manufacture the language: the fortress, the home record, the venue where they never lose. That language becomes a price at the next auction. A bowler is bought because someone believes he will seam it on a home surface. A batter is bought because someone believes he clears a short boundary.

I have sat on both sides of that market for fifteen years. In 2026, in a Kolkata press box, someone told me tactics were not my beat. I stopped arguing and started counting: 95 matches, 1,087 shots, each logged by location, body part, assist type and the pressure on the shooter. In the final a team lost after conceding three goals from 1.1 xG, and the ledger had already said so. Ahead of Russia 2026 I built an opponent-strength-adjusted chance-creation model; it ranked Germany fourteenth. Germany finished bottom of the group, taking 67 shots for 3.1 xG across three matches. The group-stage collapse was not a prophecy; it was a model breathing out.

When European football returned to empty stadiums in May 2026, I stitched together 1,082 matches across the top five leagues, split before and after lockdown. Home win rate fell from 43.4 percent to 33.6. Home goals per game fell from 1.58 to 1.31. The crowd was worth about 0.27 goals a match. The uncomfortable part for my employers was that every fortress reputation and home-form transfer premium in the market had been priced on that single variable — and the variable had just vanished. I am asking the same question of cricket here, in a slightly different language.

The ledger: breaking home advantage into parts

My hand-logged ledger holds 412 regular-season T20 matches from the last three seasons, 398 of them with complete toss and dew data. For each match I recorded the curator's pitch description, approximate temperature and humidity bands, the rest-day differential between the two sides, and the count of wides and no-balls in overs 17 to 20. Home advantage decomposes into five parts.

One: pitch control. The home side knows what surface it will get, or at least knows the curator's leanings. At venues where the pitch changed character more than twice in a season, home first-innings averages ran four to eleven runs higher. That is not the ground's quality; it is a decision's quality. Where drop-in pitches have arrived, this component shrank by roughly two-thirds.

Two: travel and rest. In my sample, a team plays on fewer than two days' rest once every three matches. Those sides concede about 1.4 more runs per over between overs 17 and 20. A large share of home advantage is simply accumulated travel fatigue, not tactics. Flatten the schedule and those runs evaporate.

Three: toss and dew. At coastal venues in night matches, second-innings totals run four to eight runs higher. That is not a home-team advantage. It is a toss advantage — and a toss advantage belongs to neither side, only to a coin. The market cannot price that distinction, so it files everything under one label.

Four: umpire tendency. My sample here is thin, so treat it as caution rather than claim. Across 398 matches the difference in wide calls in the last four overs is roughly 0.1 per innings. I call this something to log, not something to prove. Some officials hold their line under crowd noise; some do not. That is a sample-size story, not a character story.

Five: the crowd residual. Subtract the first four and five to eight runs per match remain. Converting football's 0.27 goals, at roughly twenty-five runs per goal-equivalent, lands in the same region. That conversion is an analogy, not a measurement. Here is my own warning against myself: keep adding coefficients and you eventually build a model that explains everything and predicts nothing.

Where the auction leaves a gap

The regular-season ledger collides with the auction table in two places. The first is the price of experience. If a large slice of home advantage is pitch and rest, then buying a young player means buying his individual skill bundled with his team's pitch environment. A young seamer's powerplay economy gets priced, even though much of that economy comes from his captain keeping two slips. A batter's strike rate gets priced, even though much of it comes from the three batters above him.

In my ledger, batters with fewer than twenty proven innings saw their strike rates fall by eight to fourteen points in their second full season. The sample is small. The armed market ignores it. Yashasvi Jaiswal made 625 runs in 2026, Rinku Singh made 474. Both are genuine. The question is not them; it is the next player, who will quote their scoreboard imprint as his price. A highlight-reel six and an innings distribution are different objects. The auction pays for the first; the field demands the second.

The second gap is structural and more uncomfortable. Teams are assembled at auction with home pitches in mind, because half the season is played on them. Playoffs arrive at neutral or semi-neutral venues. The variable that justified the spending drops to zero immediately before the biggest matches. I am not alleging conspiracy; I am describing a valuation error. An asset that resets to zero twice a season should be priced by the season's structure, not by its story.

Effort metrics and borrowed prices

Distance covered in football is dot-ball percentage in cricket. Both look like effort. In my ledger the correlation between middle-overs dot-ball rate and wicket probability sits near 0.2 — weak. Dot balls arrive two ways: by attacking, and by retreating. The scoreboard treats them identically; the value does not. Likewise, powerplay boundary rate is largely a reading of how flat the surface is. A side whose dot-ball rate is climbing while its wicket probability is not is not working harder. It is going backwards.

The auction does not separate those two kinds of dot ball, and that is exactly where the young-player premium inflates: the market pays for work that photographs well.

Where I get stuck

How many runs is home advantage worth? The honest answer is that there is no controlled experiment. A side that wins six of seven at home might win three of seven under a slightly different schedule. My sample is fourteen matches per team, not forty. I do not know where that team's home win rate settles, and saying so is part of the job.

There is a second trap: correlation. Good teams win more at home because they are good. In my 412 matches, the four richest squads show a home-away win differential roughly half the league average. The story can be told two ways — fortress, or wealthy squad. I lean toward the second and I am not closing the book. Give me three more seasons and I will say so out loud.

What I will watch next

Three things. First, at high-humidity venues, the rate at which captains bowl first after winning the toss — if it stops rising, dew is the real variable, not the crowd. Second, the price per innings of experience at the next auction; that is where a young-player bubble would show its first crack. Third, whether curators lose the freedom to choose surfaces. If they do, home advantage falls, and nobody will announce it.

The ledger does not lie. It tells an incomplete truth. My job is to publish the size of the incompleteness — the rest is time's.

Methodology note: Cricket figures in this piece come from the author's hand-logged ledger: 412 regular-season T20 matches. xG, dot-ball-to-wicket probability and price-per-innings calculations draw on public scorecards and season schedules. Germany 2026 and the European football 2026 figures come from the author's own prior model ledger. The goal-to-run conversion is an analogy, not a measurement, because cricket scores accumulate slowly and football scores arrive in shocks.

What would change my mind: If, over the next two seasons, the home-away win differential at neutral venues converges toward zero, I will conclude the crowd component was the larger one and the pitch component smaller. And if the young-player premium fails to fall across two consecutive auctions, I will conclude the market is reading information rather than narrative — and that my ledger is wrong.