There's a Kelly calculator for simultaneous events among the betting tools on this site.
Be aware, though, that you won't find a single pro player who bets full Kelly. The theory is never questioned, but they all turn to fractional Kelly sooner or later. The reason for that is simple. The primary challenge in sports betting is not winning percentage, but sample size. As long as the sample size requirement (300-500 samples per model) is not met, models remain vulnerable to short term fluctuations. In fact, there are many players who swear by a so-called model, without realizing that the model itself is based on a short term fluctuation. That's why it is very common in, for instance, online NFL contests to see a player peak one season only to be back to average (or worse) the next season. For this reason many pros turn to MLB. A MLB team plays ten times the regular season games of a NFL team, so the sample requirement would be met ten times faster.
From this perspective Kelly is not the best answer for sports betting, unless the sample size requirement is met. When people recognize this they turn to fractional Kelly, but that still doesn't address the sample size problem. It merely sidesteps it. What is needed is a formula that includes the sample size. Personally, I combine winning percentage and Z-score (standard deviations). I simply multiply the two, and use that as percentage of BR to wager.
Thunderground Criterion: winning percentage * Z-score * BR.
In which Z-score = (wins-losses)/SQRT(wins+losses). I bet nothing with a Z-score below 2.0.
If the resulting number is too conservative for some, it can be adjusted just as the Kelly criterion is adjusted for sports betting, only this time the sample is included. Feel free to bet 'Double Thunderground'.
That didn't answer your question, but I thought I might as well add it, before you place too much faith in full Kelly.