Table:
Year

Team

Games

Passing

Rushing

Sacked

Fumbles

G
GS
Comp
Att
Pct
Yds
Avg
TD
Int
Rtg
Att
Yds
Avg
TD
Sack
Yds
Fum
Lost

2012
WAS

3
1
33
48
68.8
466
9.7
4
3
101.6
3
22
7.3
0
3
27
1
0

2013
WAS

5
3
81
155
52.3
854
5.5
4
7
58.4
4
14
3.5
0
5
32
3
2

2014
WAS

6
5
126
204
61.8
1,710
8.4
10
9
86.4
7
20
2.9
0
8
70
2
2

2015
WAS

16
16
379
543
69.8
4,166
7.7
29
11
101.6
26
48
1.8
5
26
186
9
3

2016
WAS

16
16
406
606
67.0
4,917
8.1
25
12
97.2
34
96
2.8
4
23
190
9
3

2017
WAS

16
16
347
540
64.3
4,093
7.6
27
13
93.9
49
179
3.7
4
41
342
13
5

2018
MIN

16
16
425
606
70.1
4,298
7.1
30
10
99.7
44
123
2.8
1
40
262
9
7

Total
78
73
1,797
2,702
66.5
20,504
7.6
129
65
95.0
167
502
3.0
14
146
1,109
46
22

Your task is to examine the table in the image and deliver an HTML text version of the reconstructed table.

<table border="1" cellspacing="0">
<tr> <td rowspan="2"> year </td> <td rowspan="2"> team </td> <td colspan="2"> games </td> <td colspan="8"> passing </td> <td colspan="4"> rushing </td> <td colspan="2"> sacked </td> <td colspan="2"> fumbles </td> </tr>
<tr> <td> gp </td> <td> gs </td> <td> comp </td> <td> att </td> <td> pct </td> <td> yds </td> <td> avg </td> <td> td </td> <td> int </td> <td> rtg </td> <td> att </td> <td> yds </td> <td> avg </td> <td> td </td> <td> sack </td> <td> yds </td> <td> fum </td> <td> lost </td> </tr>
<tr> <td> 2012 </td> <td> was </td> <td> 3 </td> <td> 1 </td> <td> 33 </td> <td> 48 </td> <td> 68.8 </td> <td> 466 </td> <td> 9.7 </td> <td> 4 </td> <td> 3 </td> <td> 101.6 </td> <td> 3 </td> <td> 22 </td> <td> 7.3 </td> <td> 0 </td> <td> 3 </td> <td> 27 </td> <td> 1 </td> <td> 0 </td> </tr>
<tr> <td> 2013 </td> <td> was </td> <td> 5 </td> <td> 3 </td> <td> 81 </td> <td> 155 </td> <td> 52.3 </td> <td> 854 </td> <td> 5.5 </td> <td> 4 </td> <td> 7 </td> <td> 58.4 </td> <td> 4 </td> <td> 14 </td> <td> 3.5 </td> <td> 0 </td> <td> 5 </td> <td> 32 </td> <td> 3 </td> <td> 2 </td> </tr>
<tr> <td> 2014 </td> <td> was </td> <td> 6 </td> <td> 5 </td> <td> 126 </td> <td> 204 </td> <td> 61.8 </td> <td> 1,710 </td> <td> 8.4 </td> <td> 10 </td> <td> 9 </td> <td> 86.4 </td> <td> 7 </td> <td> 20 </td> <td> 2.9 </td> <td> 0 </td> <td> 8 </td> <td> 70 </td> <td> 2 </td> <td> 2 </td> </tr>
<tr> <td> 2015 </td> <td> was </td> <td> 16 </td> <td> 16 </td> <td> 379 </td> <td> 543 </td> <td> 69.8 </td> <td> 4,166 </td> <td> 7.7 </td> <td> 29 </td> <td> 11 </td> <td> 101.6 </td> <td> 26 </td> <td> 48 </td> <td> 1.8 </td> <td> 5 </td> <td> 26 </td> <td> 186 </td> <td> 9 </td> <td> 3 </td> </tr>
<tr> <td> 2016 </td> <td> was </td> <td> 16 </td> <td> 16 </td> <td> 406 </td> <td> 606 </td> <td> 67.0 </td> <td> 4,917 </td> <td> 8.1 </td> <td> 25 </td> <td> 12 </td> <td> 97.2 </td> <td> 34 </td> <td> 96 </td> <td> 2.8 </td> <td> 4 </td> <td> 23 </td> <td> 190 </td> <td> 9 </td> <td> 3 </td> </tr>
<tr> <td> 2017 </td> <td> was </td> <td> 16 </td> <td> 16 </td> <td> 347 </td> <td> 540 </td> <td> 64.3 </td> <td> 4,093 </td> <td> 7.6 </td> <td> 27 </td> <td> 13 </td> <td> 93.9 </td> <td> 49 </td> <td> 179 </td> <td> 3.7 </td> <td> 4 </td> <td> 41 </td> <td> 342 </td> <td> 13 </td> <td> 5 </td> </tr>
<tr> <td> 2018 </td> <td> min </td> <td> 16 </td> <td> 16 </td> <td> 425 </td> <td> 606 </td> <td> 70.1 </td> <td> 4,298 </td> <td> 7.1 </td> <td> 30 </td> <td> 10 </td> <td> 99.7 </td> <td> 44 </td> <td> 123 </td> <td> 2.8 </td> <td> 1 </td> <td> 40 </td> <td> 262 </td> <td> 9 </td> <td> 7 </td> </tr>
<tr> <td colspan="2"> total </td> <td> 78 </td> <td> 73 </td> <td> 1,797 </td> <td> 2,702 </td> <td> 66.5 </td> <td> 20,504 </td> <td> 7.6 </td> <td> 129 </td> <td> 65 </td> <td> 95.0 </td> <td> 167 </td> <td> 502 </td> <td> 3.0 </td> <td> 14 </td> <td> 146 </td> <td> 1,109 </td> <td> 46 </td> <td> 22 </td> </tr>
</table>