Say the below is the graph given,

An equation of the least squares line or a regression equation is \widehat{y} = a + bx where a is the y-intercept of the line and b is the slope of the line.

As you can see there is a positive correlation between the variables, meaning as the goals scored per match increases, the number of wins increase. So we have a positive slope. The line goes down the y-intercept so the y-intercept has a negative value.

So, options A and C get eliminated, because they have a positive y-intercept.

So, the correct option must either be option B or option D,

Now to calculate the slope of the line.

Notice two points on the line (0.6,5) and (1.3,15)

Now find the slope between the two points on the line (0.6,5) and (1.3,15)

using the slope formula \frac{y_{2}-y_{1}}{x_{2}-x_{1}}

and plugging in the points (0.6,5) and (1.3,15)

we get,

\frac{y_{2}-y_{1}}{x_{2}-x_{1}} = \frac{15-5}{1.3-6} = \frac{10}{0.7} \approx 14.28.

So, option B is the best choice.

I found an answer from www.quora.com

**Football** (**Soccer**) in **England** and Wales: **How many matches are** ...

380 matches **...** Let's apply a little bit of **Graph** Theory to solve this problem. We already know that
**there are** 20 **teams** competing in the **Premier League** . Let **each** ...

For more information, see **Football** (**Soccer**) in **England** and Wales: **How many matches are** ...

Hey, can you describe the graph, instead of giving the choices?. Information on the scale of the x-axis, scale on y-axis, where the line touches the y-axis, and does the line fall as the values of x go up. and any visible point on the graph.