Confusion on difference between the $R^2$ results from the `lm()` function in R and from the Equation 

$1-rss/sst$        (1)

Ref: https://onlinecourses.science.psu.edu/stat501/node/255/


    z1 = c(0.603,0.643,0.603,0.643,0.643,0.603,0.601,0.641,0.601,0.603,0.601,0.641,0.643,0.641,0.641,0.601,0.622)
    z2 = c(0.38,0.34,0.38,0.34,0.34,0.38,0.38,0.34,0.38,0.38,0.38,0.34,0.34,0.34,0.34,0.38,0.36)
    z3= c(0.017,0.017,0.017,0.017,0.017,0.017,0.019,0.019,0.019,0.017,0.019,0.019,0.017,0.019,0.019,0.019,0.018)
    z4= c(0.503505,0.536905,0.503505,0.536905,0.581915,0.545715,0.501835,0.535235,0.501835,0.545715,0.543905 ,0.535235,0.581915,0.580105,0.580105,0.543905,0.541140)
    z5 = c(0.3420,0.3060,0.3724,0.3332,0.3060,0.3420,0.3420,0.3060,0.3724,0.3724,0.3420,0.3332,0.3332,0.3060,0.3332,0.3724,0.3384)
    z = data.frame(z1,z2,z3,z4,z5)
    y = c(35.040, 32.100, 37.800, 33.300, 31.320, 34.026, 34.140, 31.968, 36.990, 35.970, 33.870, 33.438, 33.144, 32.106, 33.660, 35.520, 33.438)

    fit = lm(y ~ z1 + z2 + z3 + z4 + z5 - 1, data = data.frame(y, z))

    e = fit$residuals
    rss = sum(e^2)
    sst = sum((y-mean(y))^2)
    1-rss/sst
> 0.9305206

    summary(fit)$r.squared
> 0.9998195


I also checked `anova(fit)`. I think the $R^2$ results from `summary(fit)$r.squared` is correct. But why is the computation from Equation (1) wrong?