How to interpret predictions from a Neural Network

I have trained a Neural Network to make prediction of outcome(Win/Lose) of a hockey game based on a few metrics. The data I have been feeding it looks like this:

Each row represents a team in one game, so two specific rows make a match.

Won/Lost   Home   Away  metric2 metric3 metric4 team1 team2 team3 team4
1          1      0      10      10      10      1     0     0      0
0          0      1      10      10      10      0     1     0      0
1          1      0      10      10      10      0     0     1      0
0          0      1      10      10      10      0     0     0      1




The predictions from the NN looks like this.
[0.12921564 0.87078434]
[0.63811845 0.3618816 ]
[5.8682327e-04 9.9941313e-01]
[0.97831124 0.02168871]
[0.04394475 0.9560553 ]
[0.76859254 0.23140742]
[0.45620263 0.54379743]
[0.01509337 0.9849066 ]

I believe I understand that the first column is for Lost(0), and second is for Won(1), but what I don't understand is: Who won against who? I don't now what to make of these predictions, do they even mean anything to me this way?

Solution

Let us take first two rows of your dataset,

Won/Lost   Home   Away  metric2 metric3 metric4 team1 team2 team3 team4
1          1      0      10      10      10      1     0     0      0
0          0      1      10      10      10      0     1     0      0

#predictions 
[0.12921564 0.87078434]
[0.63811845 0.3618816 ]

Team 1 played a game in its home and won the match. Model prediction also aligns with it because it has assigned high probability in the second column, which is the probability of winning as you mentioned.

Similarly Team 2 played a game away and lost the match. Model prediction aligns here as well!

you just mentioned that two specific rows make a match but with available information we cannot say who played with whom. Its just a model to predict the probability of winning for a particular team independently.

EDIT:

Assuming that you have data like this!

gameID          Won/Lost   Home   Away  metric2 metric3 metric4   team1 team2 team3 team4
2017020001         1          1      0      10      10      10      1     0     0      0
2017020001         0          0      1      10      10      10      0     1     0      0

You could transform the data as follows, which can improve the model.

Won/Lost  metric2 metric3 metric4 h_team1 h_team2 h_team3 h_team4 a_team1 a_team2 a_team3 a_team4
1            10      10      10      1       0        0      0         0      1        0      0

Note: won/Lost value would be for home team, which is mentioned by h_team.