I've got hold of a Javascript statistics package and done a little analysis. The following listing has the completions in bins or buckets of five years to make things a bit more manageable. Also some of the early 1970s only had a handful of successes each year so there simply aren't enough data points to make a valid analysis, even so the numbers are pretty low. The data used is from the years 1971 to 2022 inclusive.

If you aren't used to some of the terminology here's a quick explanation,

quartiles: these are the 25% and 75% points along the data. I.e. 50% of the time lie between these two points. It's a simple version of the standard deviation.

mean: the arithmetical average - add up all the times and divide by the number of items.

middle: simply the halfway point between min and max values. 1, 2, 5, 6, 10 would have a middle of 5.5

median: the middle value in the series. 1, 2, 5, 6, 10 would have a median of 5

Standard deviation: describes how the data is clustered around the mean. A low value means the data is mostly close to the mean. 68.2% of the values lie within this distance from the mean.

skewness: describes how "normal" the distribution is. Zero (more practically between -0.5 and 0.5) would be a perfectly symmetrical distribution where the mean and median are the same value. A value lower than -1 or higher than 1 indicates very skewed data. A negative value means the outliers are to the left, a positive value means the outliers are to the right.

Kurtosis: describes how much the data conforms to a normal distribution which has a value of 3. Values below this mean fewer outliers (or a higher central peak), values above 3 mean more outliers in the tails, i.e. a flatter curve.

The quartiles show a quite consistent pattern, namely that the second value, the 75% percentile is always between 23:20 and 23:40, that is 25% of all completions take more than that time. The 25% percentile is more varied, generally between 22:30 and 22:00 but does appear to be dropping in the more recent buckets. This is likely due to the larger number of very fast times in recent years. Prior to the year 2000 there were just 19 sub 18hr times but there's been double that number since then.

The skewness shows a consistent centring of times towards the slower times, which is to be expected - there are nearly twice as many finishing times in the 23:00 to 23:59 range as there are in the 22:00 to 22:59 range. (This halving actually continues down to around 17hr mark).

This "strange" distribution might make any use of standard statistics a bit awkward. It comes about because any finishing time over 24hrs has been discarded - it's a bit like analysing times for the mile and ignoring any time over four minutes.

Anyway, here's the data.

[

{

"bin": "1970 - 1974",

"count": 24,

"stats": {

"quartiles": [

21:51, // 25%

23:20 // 75%

],

"max": "23:42",

"min": "20:37",

"mean": "22:24",

"median": "22:22",

"middle": "22:10",

"stdDeviation": "01:02",

"skewness": -0.264,

"kurtosis": 1.770

}

},

{

"bin": "1975 - 1979",

"count": 113,

"stats": {

"quartiles": [

22:01,

23:21

],

"max": "23:57",

"min": "17:45",

"mean": "22:26",

"median": "22:57",

"middle": "20:51",

"stdDeviation": "01:18",

"skewness": -1.375,

"kurtosis": 4.281

}

},

{

"bin": "1980 - 1984",

"count": 182,

"stats": {

"quartiles": [

22:24,

23:34

],

"max": "23:56",

"min": "14:56",

"mean": "22:43",

"median": "23:13",

"middle": "19:26",

"stdDeviation": "01:19",

"skewness": -2.377,

"kurtosis": 10.679

}

},

{

"bin": "1985 - 1989",

"count": 333,

"stats": {

"quartiles": [

22:05,

23:25

],

"max": "23:59",

"min": "17:40",

"mean": "22:40",

"median": "22:56",

"middle": "20:49",

"stdDeviation": "01:02",

"skewness": -1.223,

"kurtosis": 4.555

}

},

{

"bin": "1990 - 1994",

"count": 242,

"stats": {

"quartiles": [

22:27,

23:38

],

"max": "23:59",

"min": "18:18",

"mean": "22:50",

"median": "23:09",

"middle": "21:08",

"stdDeviation": "01:04",

"skewness": -1.651,

"kurtosis": 5.937

}

},

{

"bin": "1995 - 1999",

"count": 241,

"stats": {

"quartiles": [

22:43,

23:35

],

"max": "23:57",

"min": "17:48",

"mean": "22:58",

"median": "23:15",

"middle": "20:52",

"stdDeviation": "00:58",

"skewness": -2.580,

"kurtosis": 11.489

}

},

{

"bin": "2000 - 2004",

"count": 100,

"stats": {

"quartiles": [

22:36,

23:39

],

"max": "23:56",

"min": "17:00",

"mean": "22:54",

"median": "23:16",

"middle": "20:29",

"stdDeviation": "01:04",

"skewness": -2.372,

"kurtosis": 11.263

}

},

{

"bin": "2005 - 2009",

"count": 290,

"stats": {

"quartiles": [

22:13,

23:32

],

"max": "23:59",

"min": "17:08",

"mean": "22:38",

"median": "23:00",

"middle": "20:33",

"stdDeviation": "01:15",

"skewness": -1.84,

"kurtosis": 6.88

}

},

{

"bin": "2010 - 2014",

"count": 376,

"stats": {

"quartiles": [

21:59,

23:29

],

"max": "23:59",

"min": "14:58",

"mean": "22:33",

"median": "22:56",

"middle": "19:29",

"stdDeviation": "01:18",

"skewness": -1.77,

"kurtosis": 7.344

}

},

{

"bin": "2015 - 2019",

"count": 479,

"stats": {

"quartiles": [

21:48,

23:30

],

"max": "23:59",

"min": "12:52",

"mean": "22:24",

"median": "22:49",

"middle": "18:25",

"stdDeviation": "01:30",

"skewness": -2.0462,

"kurtosis": 9.343

}

},

{

"bin": "2020 - 2022",

"count": 329,

"stats": {

"quartiles": [

21:39,

23:23

],

"max": "23:57",

"min": "12:22",

"mean": "22:07",

"median": "22:44",

"middle": "18:10",

"stdDeviation": "01:49",

"skewness": -1.912,

"kurtosis": 7.816

}

}

]