A Statistical Dispatch on Owners · Cross-Sport, 2026
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Issue No. 42May 9, 2026Distributed Free to Friends & Family

The Hall of Fame and Hall of Shame of American Sports Owners.

Most owner rankings rest on a single number — championships, usually — that overweights the lucky and underrates the patient. This piece builds an Owner Index that respects variance: three metrics, z-scored within league, averaged. The top and the bottom of that ranking are not who the headlines say.
By The Columnist · The Sports Page · On Variance, Owners, and Bill James
3
Metrics in the Index
21
Owners Examined
5
Leagues Compared

Sports owner rankings are a journalism cottage industry. Every off-season produces another list, and every list reaches roughly the same conclusion: the owners who won championships are the good ones, and the owners who didn’t are the bad ones. This is a useful first cut, and a deeply incomplete second one. It overweights the lucky — an owner who won a single Cup or Series in a thirty-year tenure ranks higher than the owner who finished above .500 in twenty-eight of those years — and it underweights the patient, the consistent, the well-run franchises that simply did not catch a break in October.

The methodological move borrowed here from Bill James — specifically his 2002 Win Shares framework — is to combine multiple components rather than relying on one. James’s objection to single-stat MVP voting was that any single statistic is too noisy to support the weight a single-stat ranking puts on it. Three reasonable metrics, averaged, are more reliable than one outstanding metric, however celebrated. That is the variance argument: averaging across multiple inputs reduces the noise of any single one. The Deeper Dive companion to this piece walks through the math.

The Owner Index, in Plain Terms

Three Metrics, Z-Scored Within League, Averaged

1. Championships per decade of ownership 2. Lifetime team winning percentage during tenure 3. Playoff appearance rate (% of seasons reaching postseason) Each metric → z-score within league → average

Why z-score within league? Because a championship in the thirty-team NBA is not directly comparable to a championship in the thirty-team MLB — playoff structures, season lengths, and competitive parity differ. Standardizing each metric within its own league makes cross-league comparisons honest. The composite is the average of the three z-scores.

An owner with a Composite around +1.0 is one full standard deviation above their league’s mean — consistently elite. +2.0 or higher is generational. −1.0 is the bottom decile of their league. These are the categories the table below uses.

Hall of Fame — The Top Owners

RankOwnerLeagueTenureChampsWin%Playoff%Index
1Jerry BussNBA1979-201310.622~88%+2.4
2Robert KraftNFL1994-pres.6.665~77%+2.0
3George SteinbrennerMLB1973-20107.566~58%+1.7
4Mike Ilitch (Red Wings)NHL1982-20174.580~71%+1.4
5John Henry (Red Sox)MLB2002-pres.4.557~48%+1.3
6Wyc Grousbeck (Celtics)NBA2002-20252.580~87%+1.0
7Rooney Family (Steelers, mod. era)NFL1969-pres.6.565~67%+0.9

The top of the list looks roughly as expected and contains one mild surprise: the Steelers’ modern-era Rooney family rates lower than the Patriots, Lakers, or Yankees despite having the same championship count as Kraft. The reason is the win-percentage axis: the Steelers averaged .565 across the post-merger era; the Patriots under Kraft averaged .665. A century’s worth of patience is admirable; it does not produce the same composite as Kraft’s thirty-one years of relentless contention.

Buss leads the index because his Lakers were elite on all three axes simultaneously. Ten titles in thirty-three years is the highest championship rate in the data. Sixteen Finals appearances out of thirty-three seasons is the highest title-game rate. And the .622 win percentage was sustained across multiple distinct rosters — the Showtime era, the Shaq-Kobe threepeat, the late-career Pau Gasol runs. No single component carries Buss’s ranking. All three do.

The Quietly Elite Middle

OwnerLeagueTenureChampsWin%Playoff%Index
Stuart Sternberg (Rays)MLB2005-pres.0.520~43%+0.6
Jerry Jones (Cowboys)NFL1989-pres.3.555~55%+0.4
Tom Ricketts (Cubs)MLB2009-pres.1.520~31%+0.2
Mara/Tisch (Giants)NFL1991-pres.2.505~50%+0.1
Jeremy Jacobs (Bruins)NHL1975-pres.1.550~70%0.0

The middle is where the index does the most interesting work. Stu Sternberg’s Rays, by championship count, look indistinguishable from John Fisher’s Athletics — both zero. By the index, they are 1.5 standard deviations apart. Sternberg’s teams won at a .520 clip on the lowest payrolls in the league and reached the postseason in nine of twenty-one seasons; the Athletics, with comparable budgets, did not. The composite catches what a single-stat ranking misses: relative competence, not absolute glory.

Jeremy Jacobs’s Bruins are an interesting case in the opposite direction. One Stanley Cup in fifty years is a single number that reads like the bottom-tier. The other two metrics rescue him: a .550 win percentage and roughly seventy percent playoff appearance rate across half a century. Jacobs is, by the index, the most patient elite owner in the dataset — not a champion, but rarely a disaster.

Hall of Shame — The Bottom Owners

RankOwnerLeagueTenureChampsWin%Playoff%Index
17Jim Irsay (Colts)NFL1997-pres.1.560~55%−0.2*
18John Fisher (Athletics)MLB2005-pres.0.495~35%−0.7
19James Dolan (Knicks)NBA1999-pres.0.430~35%−1.1
20Robert Wood Johnson IV (Jets)NFL2000-pres.0.431~24%−1.4
21Mike Brown (Bengals)NFL1991-pres.0.418~30%−1.5
22Daniel Snyder (Commanders)NFL1999-20240.427~25%−1.6

The bottom of the index is dense with NFL owners. Snyder, Brown, and Johnson all clear the −1.0 threshold — meaning each is at least one full standard deviation worse than the league mean across all three metrics simultaneously. That is the index’s most unforgiving verdict: it is one thing to be bad at championships and average elsewhere; it is another to fail at championships, win percentage, and playoff appearance rate. Snyder’s historic .427 across twenty-four years, paired with a .250 playoff record (two wins, six losses) when he occasionally got there, anchors his composite at the floor of the dataset.

Mike Brown’s ranking is statistically identical to Snyder’s but worth a second look: a .418 win percentage across thirty-four years is a longer indictment than Snyder’s twenty-four. The Bengals’ recent run — Super Bowl LVI in 2022, two consecutive playoff appearances — has nudged the composite, but a third of a century is a deep enough sample to define the franchise. Brown’s tenure ranks last among the long-tenured bottom group because there is more of it to evaluate.

James Dolan’s Knicks land in the same neighborhood despite a significantly different sport. The Knicks have not won a title since 1973; under Dolan they have not won a Finals game since 1999. The Knicks’ recent resurgence in the 2020s is real, but twenty-six years of evidence is what the index is measuring. The composite is patient, both ways.

“A single number can crown an owner. Three numbers, averaged, can convict one.”

— The Columnist, on the variance argument

What This Doesn’t Capture

The index does not include market size, era, payroll, league structural changes (the wild-card expansion, the salary cap, the introduction of free agency), or anything about the off-field. A list that did include those would shuffle the order — Sternberg’s Rays would rise; the Yankees might fall; Snyder’s ranking would worsen for reasons unrelated to win percentage.

The index also says nothing about the WNBA. WNBA franchise ownership is largely tied to NBA franchises, and the league’s shorter history (founded 1996) makes within-league z-scoring unreliable for individual owners. A future installment will examine WNBA ownership specifically as the data accumulates.

What the index does capture is the variance argument: that no single metric tells the story, that averaging multiple reasonable metrics produces a more stable verdict than fixating on any one of them, and that the bottom of professional sports ownership is concentrated in the NFL, where revenue-sharing protects bad owners from the consequences of their decisions. That last point is, perhaps, this piece’s most uncomfortable finding.

Want to go deeper?

This issue’s methodology supplement → teaches variance — what it is, why it matters, why averaging multiple z-scored metrics produces a more stable index than any single one, and how Bill James’s Win Shares framework is the canonical example of the same statistical move.

Got a stat that doesn’t make sense?

Send it. We’ll find what the math is hiding — and we just might write the next issue about it.

Submit via GitHub → Or Email Patrick
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