BobP says something that is absolutely right. Abbreviated wheels are designed to ensure an at least hit eg 3 if 6 with 100% guarantee. As long as a signle generated ticket removed, then the wheel loses this 100% rate and indeed removal of a few tickets only reduces this rate well below 80%. Full wheels don't suffer from this. Each ticket is tested against an eg 6 if 6 in a pick 6 game. You keep it or remove it without affecting any such guarantee rates. If you are unlucky and you remove the winning ticket, then you simply lose the jackpot. My strategy of 30 numbers in a full wheel uses this property, so when I set up filters, my only concern is what the winning ticket should look like and therefore keep only those combinations that conform with my filters. Regarding your 1st question Relowe, I think you'd like to hear that the program can handle very easily any size of wheels (even more than 1 million generated tickets). Producing such wheels requires less than 0.1 secs! Applying a large set of filters (more than 50) is ultra-fast too (more than 0.3 million ticket checks/sec - depends on your power of your CPU of course). So you don't have to worry about it. About your 2nd question, hopefully, there are tools in the program that allow to test the effectiveness of any filter and get an understanding if it is good to use or not. So, you can decide to use or not a filter after extensively testing it. I think this is a good help.
Back in abbreviated wheels: The big question is if we can do any filtering on such wheels. Common sense says no because we'll effectively ruin the guarantee offered by that wheel. I'll not disagree with that right now. Also the inability to filter from such a wheel, makes us looking for really optimized wheels (as few tickets as possible). To get an insight of tickets in an abbreviated wheel, I'll use an example (here 3 if 5 wheel):
To have an 100% guarantee on a 3 if 5 wheel, we have to cover all possible 3-number sets. This means any combination of 1-2-3, 1-2-4, etc. Assume now that a generated ticket in such a wheel is
3 5 8 12 16.
This ticket covers 3-5-8, 3-5-12, 3-5-16, 3-8-12, 3-8-16, 3-12-16, 5-8-12, 5-8-16, 5-12-16, 8-12-16
If any such 3-number set is included in the winning draw, then this ticket will win the guaranteed prize (there might be others tickets in the wheel which produce some of these combinations - the more, the worse the wheel design is=more required tickets for 100% guarantee).
In overall, each ticket in the wheel covers 10 combinations and all tickets in an abbreviated wheel will cover all possible 3-number combinations (for a 3 if 5 wheel). To get an understanding how many such 3-number combinations exist in a 3 if 5 wheel, we have to define how many numbers picked. Let's say 30 picked numbers. So, all the 3-number combinations in a 30 numbers 3 if 5 wheel is: 30C3=4060. So, by removing the above ticket only, your least guarantee now is (4060-10)/4060=99.75%.
This is least guarantee because some of the 3-number combinations might be covered by other tickets of he wheel (the current world record for 5,30,3,5 is 102 tickets).
So, to have your filtered abbreviated wheel produce an at least 80% guarantee, this means we have to remove the following number of tickets from our wheel. (4060-x)/4060>=0.8 => x<=812. So, if every ticket covers 10 3-number combinations, we can effectively remove 812/10=81 tickets and still have an at least 80% coverage (which means we have 102-81=21 tickets left for at least 80% guarantee in a 30 numbers 3 if 5 wheel). Now, we turned our close-cover wheel in an open-cover wheel.
So, the new question now is: is there any way to determine what 3-number combinations might be safely removed? If we can decide on that, then we can effectively remove some tickets generated from our wheel (those than contain such 3-number combinations). Surely filters like SUMS, GAPS etc cannot be used at all as they cannot focus on individual tickets and 3-number sets and examine their properties. The good news is that there is such a system! The "intelligent filtering" I talk about allows such analysis and therefore you can determine what 3-number sets can be "safely removed" meaning to remove the most unwanted 3-number sets. The process is not perfect of cousre but you can effectively remove 7-8/10 combinations that regarded as "safe to remove". The remaining 2-3/10 cannot be kept as they generated by the same ticket (unless if they exist in another ticket) but the overall performance of the process offers better guarantee than the above calculated examples because we focus on the 3-number sets that will possibly remain. I hope you get my point here.