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Construction of a neural network-based model for training data analysis and performance prediction of athletes

Shiyu Xie

Shiyu Xie

School of Sports and Health, Chongqing College of International Business and EconomicsChongqing, China
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Xie, Shiyu
  
21 mar 2025
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Publicado en línea: 21 mar 2025
Recibido: 01 nov 2024
Aceptado: 18 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0624
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© 2025 Shiyu Xie, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Action assessment system overall plan
Action assessment system overall plan

Figure 2.

Reliability test
Reliability test

Figure 3.

The curve of the difference
The curve of the difference

Measure parameters processing time comparison

Action number Time distance at (ms) This article measures the time of calculation (ms)
1 2.55 1.23
2 2.56 1.26
3 2.78 2.11
4 2.95 1.95
5 2.81 1.26
6 3.02 1.28
7 3.06 1.54
8 3.45 2.64
9 2.89 1.05
10 3.55 0.59

Fixed distance distance test

Test distance True distance Test distance True distance
0.63 0.58 1.72 1.73
0.85 0.75 1.78 1.79
1.12 1.02 1.85 1.84
1.16 1.09 1.93 1.94
1.23 1.15 2.05 2.06
1.32 1.21 2.12 2.13
1.36 1.45 2.2 2.21
1.45 1.46 2.31 2.33
1.51 1.53 2.35 2.36
1.72 1.71 2.45 2.53

Indicators after clustering

N Entropy difference Main frequency 8HZ 9HZ 10HZ 1 2 3 4 Average score Best score
A
1 0.0874 33.2512 -0.0105 0.2287 5.4123 8 5 27 -9 9.494 9.626
4 -0.0602 47.1526 1.5236 -14.2154 4.4107 8.2 4 28 4 9.485 9.578
10 0.0431 50.1245 1.6254 -1.1245 4.2157 8.3 -5 23 14 9.579 9.658
13 0.0912 40.1254 16.2546 -5.1245 15.4153 7.8 -13 16.7 8 9.647 9.824
14 0.0411 38.1245 13.1245 1.7005 14.5789 8.6 7 21.6 -2 9.558 9.684
15 0.0725 63.2564 -5.8454 6.0531 9.1456 8.4 -6 23.6 -2 9.525 9.618
B
2 -0.0985 54.9878 -4.9987 -1.2045 -10.9456 8 -3 22 -13 9.36 9.754
5 -0.0985 46.4512 -0.3907 1.3995 -17.1056 8.3 -7 31 -7 9.475 9.754
7 0.0328 49.321 1.7564 20.6145 -5.5874 9.2 -5 31.8 -15 9.615 9.836
12 0.0145 45.4512 -0.9102 5.4512 -3.8415 9.5 -14 26 -14 9.584 9.802
C
3 -0.1215 27.4516 -18.7548 5.5829 -9.3215 7.8 7 25.6 3 9.632 9.856
6 -0.0185 38.1243 -0.1234 5.1109 4.4251 8.3 6 22.3 6 9.689 9.782
8 -0.0045 24.9325 -2.1945 -1.9859 -2.0945 7.5 12 28.7 -12 9.635 9.805
9 -0.0759 24.1235 -13.4561 8.3815 -22.1393 8.2 1 16.4 -8 9.407 9.541
11 0.0086 33.7045 -0.3256 -1.8446 -3.9315 8.4 3 30.6 -5 9.659 9.761

Clustering results

Sample number categories Model test
1, 4, 10, 13, 14 A 15
2, 5, 7, 12 B
3, 6, 8, 9, 11 C

Longitudinal tracking results after clustering

Serial number Fatigue awareness symptom Self-feeling training intensity Ego degree Training mode
A
1 0.25 0.72 4 I*2, II*2, III*3
4 0.27 0.6 4 I*2, II*2, III*5
10 0.26 0.66 3 II*2, III*7, V*1
13 0.01 0.77 4 II*3, III*7, V*1
14 0.21 0.69 3 II*2, III*2, V*1
15 0.17 0.71 2 II*6, III*12, V*1
B
2 0.46 0.62 3 I*2, II*2, III*7
5 0.68 0.61 3 I*2, II*2, III*5
7 0.45 0.67 3 I*2, III*7, IV*4, V*1
12 0.87 0.69 3 II*3, III*6, V*1
C
3 0.19 0.58 4 I*2, II*2, III*4
6 0.11 0.65 4 II*2, III*8, IV*1, V*1
8 0.03 0.61 3 II*2, III*7, V*1
9 0.39 0.69 4 II*2, III*7, V*1
11 0.27 0.6 4 II*3, III*7, V*1

Multifunctional body motion test results

Sports category Frequency of motion Motion recognition rate/% Accuracy rate/%
Sit-ups 400 98.9 98.2
Lead up 400 98.8 98.5
Squat motion 400 99.3 98.9
Fixed jump 1200 94.3 87.5
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