Research Challenge: The Effect of Relative Age on Fight Results

The question of age's influence on fight results is not an easy one to address. While it's commonly known that a certain age range reflects most fighters' athletic peaks, and it's easy to observe the decline of attributes such as speed and reflexes past a given age, the number of times a fighter has blown out birthday candles doesn't consistently reflect his strength, skill level, experience/composure, etc.

Regardless, it's a curiosity that merits investigation. Here is a surface-layer summary of the data made available to us by

Winner is Younger Winner is Older All Fights
Total Fights 1489 (57%) 1111 (43%) 2600*
(T)KO Wins 559 (61%) 359 (39%) 918
Sub Wins 422 (57%) 322 (43%) 744
Dec Wins 505 (54%) 430 (46%) 935
Mean Winner's Age 27.0 31.0 28.7
Mean Loser's Age 31.8 27.1 29.8
Mean Age Difference 4.8 4.0 4.4
Mean Fight Length 08:57 09:50 09:20
* Four fights involving identically-aged fighters were omitted.
Two disqualifications and one "other" were omitted from
method-specific counts/calculations.


These preliminary figures suggest that youth holds the advantage. Across 2600 fights, the younger contestant prevailed 57% of the time. Youthful fighters also outperformed their seniors in all three methods of victory, excelling in striking-based finishes, but less so on judges' scorecards.

Some of the statistics fall under the "duh" category (obviously the average winner's age will be lower than the average loser's age when considering only bouts won by younger men), but most are at least somewhat thought-provoking. It's interesting to note, for example, that despite a tremendous total age range (16 to 51!), the overall average winner is still a full year younger than the overall average loser. Also notice the wider mean age difference across fights with more youthful victors. This could reflect yet another nod for fledgling fighters: perhaps it's easier for youngsters to win in spite of dramatic age disparities, while veterans tend to find success over more comparably seasoned opponents. Finally, there appears to be a faint correlation between bout length and winner's age (relative to that of his inferior). Younger winners clock their victories about a minute quicker than older winners, sensible, given the former's inclination toward (T)KO wins and the latter's toward decisions.

Though these figures are quite harmonious, they are too broad to be definitive. Consistent trends across narrower intervals would present a more convincing argument, and that's what I will attempt to uncover.

Where to Begin?


After some false starts and a fair amount of thought, I decided that absolute age should not be the primary variable for this study. As the question at hand involves not merely the advantages and disadvantages experienced at each age, but how they compare between fighters of different ages, Age Difference throughout all 2600 fights should prove to be the most enlightening X axis variable.

Also, as all of the graphs will express Win% in some context or another, and the early edge thus far has gone to the younger fighters, all Y axes will measure younger fighters' win rates. High values and rising trends will favor them, while falling trends will look good for the old guard.

What Weird Graphs Did I Make This Time?


A fair question, and one that you'll wish I didn't force you to ask.

When constructing a histogram, the most common and attractive feature to include is equal bin width. That is to say, you might demonstrate how many miles you drove every three days, or how much money you spent every two weeks. This is great when expressing frequencies or amounts, but not so much for percentages (ie. Win%). Say you're tracking percentage of successful free throws per foot of shooters' height, and your 5'-6' bar reads 80% while your 6'-7' bar reads 60%. This information is not particularly helpful. How many attempts were made within each range of height? Is the 80% score for 4 baskets out of 5 shots, while the 60% score reflects 45 out of 75?

To that end, I decided to forgo equal bin width in favor of equal number of records (fights) per bin (bar). And don't think for a second that this choice wasn't informed by the nice, even total of 2600 fights. Their widths along the Y axis may vary wildly, but each of the 10 bins will represent exactly 260 fights which featured an age difference within the expressed range. Here's the first Win% histogram, followed by an informative table and a written walkthrough:

Younger Fighters' Win% Across Age Differences
(Age Difference in Years)


Bin Info for Win% Graph (2600 total fights)
Bin # 1 2 3 4 5 6 7 8 9 10
Bin Size (fights) 260 260 260 260 260 260 260 260 260 260
Bin Range (years) 0.0 to 0.7 to 1.4 to 2.1 to 2.9 to 3.7 to 4.6 to 5.7 to 7.2 to 9.3 to 23.9
Bin Width (years) 0.7 0.8 0.7 0.8 0.7 1.0 1.1 1.4 2.1 14.6


Before we address the clear trend, let's get acclimated to exactly what the graph portrays. As you can see, there are 10 bins, each numbered from left to right. Each bin represents 260 fights (2600 total divided by 10), while the physical width of each bin expresses the range of age differences occupied by its respective 260 fights. The physical height of a bin shows what percentage of those fights were won by the younger participant. So the narrow Bin #1 actually reflects a very densely populated range of age differences (a single day to 0.7 years, or just 8 1/2 months). All the way to the right, Bin #10, although it appears massive, houses not a single fight more than any other bin. Its 260 records are merely scattered thinly throughout an expansive range (age differences from 9.3 years to a baffling 23.9: Frye vs. Herman maybe?).

The graph, I feel, speaks for itself. Across the ten ranges, younger fighters never win less than 50% of the time. The only fights in which older fighters are even that competitive are ones where the age difference between contestants is less than 9 months (Bin #1). The victorious older fighters in this range are not necessarily "old" at all: one is as likely to be a 23 year-old beating a 22 year-old as a 46 year-old beating a 45 year-old.

The real case is made by the constant upward trend (Bin #7 being the lone, minor exception) and the younger fighters' whopping 70% win rate throughout the final bin. This final subset is where you'll find 25 year-olds beating up 40 year-olds, which they're doing more than twice as often as not.

This wasn't the most sophisticated approach, but I find the results reasonably convincing. The histogram, combined with the sample-wide averages discussed further above, really seems to suggest that the younger a fighter is compared to his opponent, the better.




Just for fun (?), I patched together the same graph/table combination for the three major categories of fight conclusion. (T)KO results closely resemble those of the entire sample, while submission and decision victories are a bit more sporadic. Also notice that I had to adjust the number of bins, and their size and widths, for each table, depending on the subset size. For example, 918 fights ended in a knockout or TKO, which isn't evenly divisible by 10. Instead, I graphed 9 bins, each expressing 102 fights. (It was just a stroke of luck that I was able to divide evenly for all three subsets.)



Appendix A: Younger Fighters' (T)KO Win% Across Age Differences
(Age Difference in Years)


Bin Info for (T)KO Win% Graph (918 fights)
Bin # 1 2 3 4 5 6 7 8 9
Bin Size (fights) 102 102 102 102 102 102 102 102 102
Bin Range (years) 0.0 to 0.8 to 1.7 to 2.6 to 3.5 to 4.7 to 5.7 to 7.4 to 9.3 to 21.6
Bin Width (years) 0.8 0.9 0.9 0.9 1.2 1.0 1.6 1.9 12.3



Appendix B: Younger Fighters' Submission Win% Across Age Differences
(Age Difference in Years)


Bin Info for Submission Win% Graph (744 fights)
Bin # 1 2 3 4 5 6 7 8
Bin Size (fights) 93 93 93 93 93 93 93 93
Bin Range (years) 0.0 to 0.9 to 1.9 to 2.8 to 3.7 to 5.0 to 6.7 to 9.0 to 23.9
Bin Width (years) 0.9 1.0 1.0 0.9 1.2 1.7 2.3 14.9



Appendix C: Younger Fighters' Decision Win% Across Age Differences
(Age Difference in Years)


Bin Info for Decision Win% Graph (935 fights)
Bin # 1 2 3 4 5 6 7 8 9 10 11
Bin Size (fights) 85 85 85 85 85 85 85 85 85 85 85
Bin Range (years) 0.0 to 0.6 to 1.1 to 1.8 to 2.4 to 3.0 to 3.7 to 4.5 to 5.5 to 6.8 to 8.7 to 17.3
Bin Width (years) 0.5 0.5 0.7 0.6 0.6 0.6 0.9 1.0 1.2 1.9 8.6

\The FanPosts are solely the subjective opinions of Bloody Elbow readers and do not necessarily reflect the views of Bloody Elbow editors or staff.

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