I've written my own Reversi player, based on the MiniMax algorithm, with Alpha-Beta pruning, but in the first 10 moves my evaluation function is too slow. I need a good early-game evaluation function.

I'm trying to do it with this matrix (corresponding to the board) which determines how favourable that square is to have:

   { 30, -25, 10, 5, 5, 10, -25,  30,},
   {-25, -25,  1, 1, 1,  1, -25, -25,},
   { 10,   1,  5, 2, 2,  5,   1,  10,},
   {  5,   1,  2, 1, 1,  2,   1,   5,},
   {  5,   1,  2, 1, 1,  2,   1,   5,},
   { 10,   1,  5, 2, 2,  5,   1,  10,},
   {-25, -25,  1, 1, 1,  1, -25, -25,},
   { 30, -25, 10, 5, 5, 10, -25,  30,},}; 

But it doesn't work well.

Have you even written an early-game evaluation function for Reversi?