Marathon Statistics by State and Finish Rate

Marathon statistics at a glance

Marathon results can look repetitive until you start comparing the counts behind them. The Boston Marathon 2026 Statistics dataset shows how many runners entered, started, and finished by state and territory, and the gaps between those three stages tell a precise story about participation and completion.

Table of contents

• Fast facts
• What the dataset measures
• States with the biggest entry totals
• States with the strongest finish rates
• Where the drop-offs were largest
• Compact comparison table
• How to read the numbers
• Patterns worth noticing

Fast facts

• The dataset covers 55 geographic entries, from states to territories and Armed Forces Europe (Boston Marathon 2026 Statistics).
• Massachusetts had the highest entry total at 4,692 entered, 4,490 started, and 4,352 finished (Boston Marathon 2026 Statistics).
• California was next at 2,036 entered, 1,836 started, and 1,818 finished (Boston Marathon 2026 Statistics).
• New York recorded 1,866 entered, 1,694 started, and 1,686 finished (Boston Marathon 2026 Statistics).
• Ohio posted the highest listed finish rate at 99.8% with 598 entered, 554 started, and 553 finished (Boston Marathon 2026 Statistics).
• Several entries reached 100.0% finished, including Hawaii, Idaho, Iowa, Kansas, Mississippi, Montana, Oklahoma, South Dakota, Vermont, West Virginia, Wyoming, Armed Forces Europe, Puerto Rico, and Virgin Islands (Boston Marathon 2026 Statistics).

What the dataset measures

This dataset is best read as a participation pipeline. It starts with entered runners, then shows how many actually started, and then how many were finished and recorded as finished in the table. That structure matters because a large entry number does not automatically mean a large finish number, and a high finish percentage does not always mean the largest overall volume.

The source label is explicit throughout: these are the Boston Marathon 2026 Statistics. That makes the dataset useful for comparing both scale and conversion across states and territories without mixing in outside assumptions or unrelated marathon data.

A useful shorthand for reading the rows is simple:

• entered tells you interest or qualification into the dataset,
• started tells you who moved from entry to the starting line,
• finished tells you who completed the listed result.

The gap between entered and started is just as meaningful as the gap between started and finished. For example, some places show very high entry totals but still have a noticeable reduction before the start, while others convert nearly every entered runner into a starter and finisher.

States with the biggest entry totals

The most obvious pattern in the list is concentration at the top. A handful of states account for the largest entry totals, and the difference between them is wide enough to matter.

Massachusetts leads by a large margin with 4,692 entered, 4,490 started, and 4,352 finished (Boston Marathon 2026 Statistics). California is the next largest entry total at 2,036 entered, 1,836 started, and 1,818 finished (Boston Marathon 2026 Statistics). New York follows with 1,866 entered, 1,694 started, and 1,686 finished (Boston Marathon 2026 Statistics). Texas also sits in the four-digit range with 1,050 entered, 946 started, and 937 finished (Boston Marathon 2026 Statistics). Illinois adds another large cluster with 793 entered, 720 started, and 710 finished (Boston Marathon 2026 Statistics).

Those five alone show the dataset’s scale hierarchy clearly. Massachusetts is not just first; it is more than double California’s entry count and well above the rest of the list. That makes it the central anchor in any quick read of the statistics.

A second tier sits just below the top four-digit and high-three-digit thresholds. Florida recorded 740 entered, 671 started, and 659 finished (Boston Marathon 2026 Statistics). Pennsylvania had 739 entered, 669 started, and 664 finished (Boston Marathon 2026 Statistics). New Jersey reached 675 entered, 617 started, and 607 finished (Boston Marathon 2026 Statistics). Ohio posted 598 entered, 554 started, and 553 finished (Boston Marathon 2026 Statistics). Colorado reported 591 entered, 535 started, and 531 finished (Boston Marathon 2026 Statistics).

That middle band matters because it shows how deep the dataset remains beyond the top few leaders. The rankings are not just about the top three; there is a long block of states with substantial counts that remain tightly grouped.

States with the strongest finish rates

The highest finish rates in the dataset appear across both small and mid-sized entry totals. A perfect finish rate of 100.0% appears in multiple rows, which means every listed starter in those rows is also listed as finished (Boston Marathon 2026 Statistics).

The 100.0% entries are:

• Hawaii: 57 entered, 53 started, 53 finished (Boston Marathon 2026 Statistics)
• Idaho: 85 entered, 77 started, 77 finished (Boston Marathon 2026 Statistics)
• Iowa: 103 entered, 91 started, 91 finished (Boston Marathon 2026 Statistics)
• Kansas: 78 entered, 70 started, 70 finished (Boston Marathon 2026 Statistics)
• Mississippi: 30 entered, 28 started, 28 finished (Boston Marathon 2026 Statistics)
• Montana: 39 entered, 37 started, 37 finished (Boston Marathon 2026 Statistics)
• Oklahoma: 89 entered, 78 started, 78 finished (Boston Marathon 2026 Statistics)
• South Dakota: 34 entered, 28 started, 28 finished (Boston Marathon 2026 Statistics)
• Vermont: 84 entered, 81 started, 81 finished (Boston Marathon 2026 Statistics)
• West Virginia: 40 entered, 34 started, 34 finished (Boston Marathon 2026 Statistics)
• Wyoming: 13 entered, 12 started, 12 finished (Boston Marathon 2026 Statistics)
• Armed Forces Europe: 2 entered, 2 started, 2 finished (Boston Marathon 2026 Statistics)
• Puerto Rico: 32 entered, 29 started, 29 finished (Boston Marathon 2026 Statistics)
• Virgin Islands: 3 entered, 2 started, 2 finished (Boston Marathon 2026 Statistics)

That list is important because it reveals that perfection is not limited to the smallest sample sizes. Hawaii, Iowa, and Oklahoma all combine substantial enough counts with a perfect finish conversion from starters to finishers (Boston Marathon 2026 Statistics).

Several other states sit just below perfection with extremely strong rates:

• Ohio: 598 entered, 554 started, 553 finished, 99.8% finished (Boston Marathon 2026 Statistics)
• North Carolina: 541 entered, 483 started, 481 finished, 99.6% finished (Boston Marathon 2026 Statistics)
• Oregon: 292 entered, 266 started, 265 finished, 99.6% finished (Boston Marathon 2026 Statistics)
• New York: 1,866 entered, 1,694 started, 1,686 finished, 99.5% finished (Boston Marathon 2026 Statistics)
• Missouri: 197 entered, 190 started, 189 finished, 99.5% finished (Boston Marathon 2026 Statistics)

Those rows matter because they show high completion at meaningful scale. When a state combines hundreds or even thousands of entries with a finish rate above 99%, the dataset is signaling unusually strong consistency from the start line to the finish line.

Where the drop-offs were largest

The most noticeable drop-offs appear where the started and finished numbers sit a bit farther below the entry total or where the finish percentage is lower than the rest of the table. That does not mean the performance is weak; it simply means the conversion path has more losses than the other rows.

The lowest finish percentage in the dataset is North Dakota at 92.3% finished, with 14 entered, 13 started, and 12 finished (Boston Marathon 2026 Statistics). That is the clearest low end of the table.

A few other rows sit below the 97% band:

• Massachusetts: 4,692 entered, 4,490 started, 4,352 finished, 96.9% finished (Boston Marathon 2026 Statistics)
• Connecticut: 385 entered, 353 started, 342 finished, 96.9% finished (Boston Marathon 2026 Statistics)
• Alabama: 118 entered, 109 started, 105 finished, 96.3% finished (Boston Marathon 2026 Statistics)
• Arkansas: 74 entered, 66 started, 64 finished, 97.0% finished (Boston Marathon 2026 Statistics)
• Maine: 183 entered, 170 started, 165 finished, 97.1% finished (Boston Marathon 2026 Statistics)
• Georgia: 301 entered, 274 started, 266 finished, 97.1% finished (Boston Marathon 2026 Statistics)
• Rhode Island: 160 entered, 150 started, 146 finished, 97.3% finished (Boston Marathon 2026 Statistics)
• South Carolina: 210 entered, 196 started, 191 finished, 97.5% finished (Boston Marathon 2026 Statistics)
• New Mexico: 45 entered, 42 started, 41 finished, 97.6% finished (Boston Marathon 2026 Statistics)

Massachusetts belongs in both the top-volume and lower-finish-rate conversations because of its sheer scale. Even with 96.9% finished, it still produces the largest finished total in the dataset at 4,352 (Boston Marathon 2026 Statistics). That is the key distinction: percentage efficiency and absolute output are not the same thing.

Compact comparison table

The rows below give a quick side-by-side look at several useful reference points in the dataset.

Geography	Entered	Started	Finished	Finish rate
Massachusetts	4,692	4,490	4,352	96.9%
California	2,036	1,836	1,818	99.0%
New York	1,866	1,694	1,686	99.5%
Texas	1,050	946	937	99.1%
Ohio	598	554	553	99.8%
North Dakota	14	13	12	92.3%
Hawaii	57	53	53	100.0%
Oregon	292	266	265	99.6%

The table shows three different kinds of story at once. Massachusetts dominates volume. Ohio and Oregon stand out for unusually strong conversion. North Dakota shows how a very small count can produce the weakest percentage in the list without changing the broader scale of the dataset.

How to read the numbers

One of the easiest mistakes with marathon statistics is to focus on a single column. The entered count alone does not tell you who reached the start line. The finished count alone does not show how many were in the original pool. The percentage alone does not tell you how large the underlying group was.

A better read is to compare all three together. That lets you separate these situations:

• high entry, high finish, and high conversion,
• moderate entry with exceptional finish rate,
• small entry with perfect conversion,
• large entry with a few more losses along the way.

California is a good example of high volume with strong efficiency. It has 2,036 entered, 1,836 started, and 1,818 finished, which keeps the finish rate at 99.0% (Boston Marathon 2026 Statistics). New York is similar, but with slightly lower absolute volume and an even higher finish rate of 99.5% (Boston Marathon 2026 Statistics). Ohio is smaller than either of those, but its 99.8% finish rate makes it one of the sharpest conversion rows in the dataset (Boston Marathon 2026 Statistics).

Patterns worth noticing

Several patterns repeat across the full list.

First, the states with the largest entry totals generally also have the largest finished totals. That sounds obvious, but the dataset confirms it clearly. Massachusetts, California, New York, Texas, and Illinois all appear near the top of both entry and finish counts (Boston Marathon 2026 Statistics).

Second, high finish rates are not reserved for one region or one population size. Perfect 100.0% finishes show up in large and small entries alike, from Hawaii and Idaho to Puerto Rico and Armed Forces Europe (Boston Marathon 2026 Statistics). That variety suggests the dataset is more nuanced than a simple “big states win, small states lose” pattern.

Third, the gap between entered and started can be more informative than the gap between started and finished. Many rows show only a small decline after the start line, which means the main attrition happens earlier in the pipeline. For example, Florida goes from 740 entered to 671 started and then 659 finished (Boston Marathon 2026 Statistics). Pennsylvania moves from 739 entered to 669 started and then 664 finished (Boston Marathon 2026 Statistics). Those losses are visible, but they are modest compared with the full scale of the states involved.

Fourth, the list contains enough rows to make comparisons by band useful. The top four-digit group, the mid-hundreds, and the perfect-rate outliers all tell different parts of the same story. That is why marathon statistics are more useful when read as a dataset rather than as isolated records.

Finally, the source labels matter. Because every row is tied to the Boston Marathon 2026 Statistics, the safest interpretation is to stay inside that data boundary and avoid adding assumptions beyond the counts and percentages shown. That keeps the analysis grounded in the actual source rather than in generic marathon commentary.