How to Predict Sporting Matches Using Probability | Beginner Excel Tutorial 

Thanks lad, appreciate it.

Thank you!!!

You're welcome lad!

Thank you very much!!!

That's awesome lad!

Thanks LAD

Thanks for watching lad!

Thanks lad.

That's why we publish! Subscribe for more lessons lad.

Aye lad.

Very true. This model has defects, the most obvious being: 1. It doesn't take into account who is playing for each team. For example, if PSG rested Messi, Mbappe and Neymar for a match, then their team attacking strength would undoubtedly decrease. However, this model doesn't take this circumstance into account. We are planning to release an 'Intermediate Excel Tutorial' which would cover this. Furthermore, this video would take into account factors such as a team's home ground advantage as well as exhibit different betting strategies.

I have plans to upload a video explaining a more advanced predicative model for the EPL. This would take into account the relative strength of each team's games and home advantage (which this video does not). I would also exhibit how to set up the model to be more visually appealing, as well as how to calculate odds for any Bet365 betting criteria (e.g. exact scoreline). Subscribe to be ready for this video!!!

@@excel_ladz that'll be awesome man, i hope you do this pretty soon

@@GuardianApe Thanks lad!

@@excel_ladz Please do, sir!!!!

Hi Bob! Yes, this formula can be used for any sport but here's how I would adjust it for American football. Unlike soccer, where every time a team scores they get 1 point, in American football a touchdown is worth 7 points (assuming a successful extra point), a field goal is worth 3 points, and a safety is worth 2 points. Take the recent Dolphins vs Jets game where Dolphins won 24-0. Dolphins didn't score 24 times in this game, they scored 3 touchdowns and 1 field goal. So the average points per score is 6. (keep reading below) Looking at historical statistics, NFL teams average around 2.5 touchdowns per game, and 1.5 field goals, and virtually no safeties. So the standard points per score is 5.5 (2.5*7+1.5*3)/(2.5+1.5). At timestamp 3:53, we are calculating the expected goals. Do all the steps exactly how I explained in the video before that. The only difference is, for the poisson distribution entries we will divide the expected points by 5.5 to get expected number of scores. For example, for the upcoming game Bills vs Jets, the expected score might be 32-10 (rounded to nearest whole number). You will find if you put exactly those numbers into the poisson distribution formula, then Jets will have a 0.01% chance of winning which is false and skewed. So, right under or beside your expected points, divide the expected points by 5.5. For Bills you will end up with about 5.8, and Jets about 1.8. Now use the poisson.dist formula on those scores. You will find that Bills now have a 75% winning, and Jets have a 4% chance with a 'draw' 21% likely. However, we will ignore the draw and instead find Bill's chance of winning by 75% divided by 75%+ 4%, and Jets chance of winning by 4% divided by 75%+4%. So our final probability spits out Jets having around a 5.5% chance of winning, with the Bills a 94.5% favourite, a much more plausible result. I hope this helps!

@@excel_ladz Thank you for your explanation ... haven’t been able to get to my computer... I will respond as soon as I plug in numbers... Thanks again... Bob

@@excel_ladz Thanks.. I have all formulas inputted BUT when I do poisson Dist the numbers are wacked out...do I use 0 in poisson dist then exp scores of 5.8? poisson.dist (0,5.8,false), poisson.dist(1,5.8,false) etc? then copy down to 15?... before that I get expected score of Bills 32..,Jets 14...any help?

Found my error Bills 83% jets 9.09%...Where did you find numbers for historical scoring? I like doing numbers BUT I just need to be pointed in right direction

@@bobnicholson6350 When I saw your comment I just glanced at the past few years on these websites: www.teamrankings.com/nfl/stat/field-goals-made-per-game?date=2016-02-08 www.teamrankings.com/nfl/stat/touchdowns-per-game If you wanted your model to be more accurate, then collecting data on individual teams and their average points per score would be beneficial instead of using a standard divisor for all teams.

Thanks for watching lad. As for this system, no. Just curious, in the future would you consider purchasing a Horse Racing Predicative Model from Excel LADZ? If you have any more questions just reply, as I'm looking to expand the channel.

@@excel_ladz Yes I'd be interested let me know some details

Hİ ..How can I have this excel, thank you..

@@sukru25141 Hi lad, if you want access to this model (and every other Excel LADZ model), join the Excel LADZ community! Sign up here: www.patreon.com/ExcelLADZ 💪

Yes, this model would be very easy and fun to create for baseball. However, due to the more individual nature of the performance of a baseball team, I advise against using this specific model for any betting purposes. In the near future, our team will look at doing a baseball-specific tutorial.

‘Goals for’ simply means the goals scored by that particular team, and ‘goals against’ includes the goals conceded by that team. Make sure you’re subscribed lad 🔥

This video could predict cricket matches, but to a very limited extent. Cricket games would require a different model, which we plan to teach on our channel in the near future! Please subscribe if you haven't already to stay updated.

@@excel_ladz thanks .. waiting for this one... 🎉😎😎

Tonight 5:00pm LAD

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