In my ongoing work with DNB (Draw No Bet) as the core pattern, I’ve recently developed a filtered subset that I call SDB (Scoreline Draw Bet). While DNB covers a broad range of matches, SDB applies an additional layer of filtering on top of DNB’s criteria, narrowing the focus to a smaller set of games that appear to have a higher probability of ending in a draw.

This subset has shown an interesting early tendency: across its (develop + test) phase, SDB has recorded 3W, 7D, 2L with average odds around 3.5. That translates to a 58.33% success rate, which is highly profitable if sustained — but with such a small sample, I remain cautious.

It’s important to note that SDB is not retroactively pulled from DNB’s draws. Instead, it emerges naturally from a refined selection process, meaning the games in SDB could theoretically be placed as both a DNB and a draw bet. In the case of a draw, DNB would refund while SDB would score a profit, giving me the option to hedge safety with upside.

DNB itself continues to perform well, with 26W, 17D, 6L — an 81.25% no-lose rate over 49 games. If SDB proves itself over a larger sample, it could serve as both a standalone pattern and a profit amplifier to DNB. My plan is to continue tracking SDB as its own dataset, while noting its impact when overlaid with DNB in live conditions.

In my ongoing work with DNB (Draw No Bet) as the core pattern, I’ve recently developed a filtered subset that I call SDB (Scoreline Draw Bet). While DNB covers a broad range of matches, SDB applies an additional layer of filtering on top of DNB’s criteria, narrowing the focus to a smaller set of games that appear to have a higher probability of ending in a draw.

This subset has shown an interesting early tendency: across its (develop + test) phase, SDB has recorded 3W, 7D, 2L with average odds around 3.5. That translates to a 58.33% success rate, which is highly profitable if sustained — but with such a small sample, I remain cautious.

It’s important to note that SDB is not retroactively pulled from DNB’s draws. Instead, it emerges naturally from a refined selection process, meaning the games in SDB could theoretically be placed as both a DNB and a draw bet. In the case of a draw, DNB would refund while SDB would score a profit, giving me the option to hedge safety with upside.

DNB itself continues to perform well, with 26W, 17D, 6L — an 81.25% no-lose rate over 49 games. If SDB proves itself over a larger sample, it could serve as both a standalone pattern and a profit amplifier to DNB. My plan is to continue tracking SDB as its own dataset, while noting its impact when overlaid with DNB in live conditions.