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Research and application of constructing football training linear programming based on multiple linear regression equation


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Fig. 1

Division of football match fields.
Division of football match fields.

The correlation between the outcome of the game and the indicators

Index Sample size Correlation coefficient Significance Index Sample size Correlation coefficient Significance

X1 400 0.475 0.047 X27 400 −0.683 0.002
X2 400 0.976 0 X28 400 −0.183 0.469
X3 400 0.535 0.022 X29 400 0.304 0.22
X4 400 0.683 0.002 X30 400 0.122 0.63
X5 400 0.545 0.019 X31 400 0.011 0.913
X6 400 0.416 0.086 X32 400 0.34 0.167
X7 400 0.131 0.604 X33 400 0.452 0.06
X8 400 0.098 0.7 X34 400 0.657 0.003
X9 400 0.024 0.924 X35 400 0.354 0.15
X10 400 0.085 0.737 X36 400 −0.219 0.383
X11 400 0.438 0.069 X37 400 −0.280 0.261
X12 400 0.523 0.026 X38 400 −0.173 0.493
X13 400 0.401 0.099 X39 400 0.427 0.077
X14 400 0.617 0.006 X40 400 −0.527 0.025
X15 400 0.377 0.123 X41 400 −0.401 0.099
X16 400 0.295 0.235 X42 400 −0.450 0.061
X17 400 0.413 0.088 X43 400 0.225 0.369
X18 400 0.402 0.098 X44 400 0.228 0.363
X19 400 0.061 0.809 X45 400 −0.085 0.737
X20 400 0.511 0.03 X46 400 0.182 0.469
X21 400 0.547 0.019 X47 400 0.267 0.284
X22 400 0.206 0.411 X48 400 0.383 0.117
X23 400 0.802 0 X49 400 0.389 0.111
X24 400 −0.012 0.962 X50 400 0.073 0.774
X25 400 −0.976 0 X51 400 0.152 0.548
X26 400 −0.559 0.016 X52 400 −0.152 0.548

Regression coefficient table

Variable Parameter estimate Standard error Type II SS F value Significance (Pr > F)

Intercept 0.07407 0.01719 0.00142 18.57 <0.0001
X6 0.27741 0.02728 0.00790 103.40 <0.0001
X13 0.09219 0.01663 0.00235 30.72 <0.0001
X2 0.13100 0.02305 0.00247 32.30 <0.0001
X20 0.07443 0.01342 0.00235 30.74 <.0001
X11 0.12904 0.02254 0.00250 32.77 <0.0001
X21 0.04669 0.01905 0.00046 6.01 0.0184
X23 0.06296 0.02080 0.00070 9.17 0.0042
X19 0.06853 0.02419 0.00061 8.03 0.0070

Regression analysis variance of game winning factors and game performance

Model Sum of variance Mean difference F Sig.

1 Regression 129.495 2.878 3.8880.000
Residual 37.005 0.74
Total 160.5

Stepwise regression process

Step Introduced variables Number of variables Coefficient of determination R2 Model R2 C (P) F Significance(Pr > F)

1 X6 1 0.7855 0.7855 354.351 183.10 <0.0001
2 X13 2 0.0971 0.8826 174.172 40.54 <0.0001
3 X2 3 0.0342 0.9168 111.994 19.75 <0.0001
4 X20 4 0.0269 0.9437 63.5307 22.47 <0.0001
5 X11 5 0.0174 0.9611 32.8756 20.61 <0.0001
6 X21 6 0.0072 0.9684 21.3579 10.25 0.0025
7 X23 7 0.0044 0.9728 15.0255 7.19 0.0103
8 X19 8 0.0043 0.9771 9.0000 8.03 0.0070

Regression statistics results

DF SS MS F Significance (Pr > F)

Regression analysis 8 0.14009 0.01751 229.10 <0.0001
Residual 43 0.00329 0.00007644
Total 51 0.14338
eISSN:
2444-8656
Language:
English
Publication timeframe:
Volume Open
Journal Subjects:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics