A twenty over a side cricket game that mocks as the domestic Indian competition but allows teams to field 4 foreign players in their 11 on the field. Like most T20 competitions the worst team can beat the best team with even a modest amount of luck. The best we can hope to do is grab the stats we feel are important and then apply them on the day of the game.
The IPL teams and players receive the most hype in the cricket world. What this means is a lot of betting money is gut feeling money. We need to simply use hard numbers to set our prices.
We'll go through each squad of players and pick out the stats we think are most important. We will then apply them in a way that makes sense. The nature of the competition means there are no sure things, and that's what makes it fun.
We have to be choosy in not only the stats we grab, but also how we apply them. Also we have to decide which stats to allow. Is there a difference between international and domestic stats? Should we include them both? And if so should we weigh them differently? The short answer is no.
If you want a long answer then here it is. Much has been made about the step up from domestic cricket to international cricket, but this is really just a domestic competition with some international class players in it, much like any normal domestic game. Furthermore, why does a batsman need a better international batting average when half the time he'll be facing a bowler who is not international standard.
Sure players who represent their country are higher standard players, but that should be reflected in their stats anyway if they are truly any good.
So we include all their T20 stats regardless of where they came from.
One of the problems will be players with few matches having very skewed figures. We will take note of these on the stat sheet so we can smooth them over.
Matches and Innings really only tell us how much experience the player has. The higher the number the truer all the other stats will be. To keep it simple though we can just ignore it.
Not Outs reaally doesn't concern us as this is a useless stat without knowing why they were not out.
Total Runs is not really of any concern to us as it is factored into the average anyway.
Highest Score is an interesting one. While it is handled by the average, it can also be a check for us. Players can have an average higher than their highest score, especially players who are frequently not out. To combat this we put in place a calculation. Wherever the average is higher than half of the highest score, we cut the runs down to half of the highest score. For example a player with a top score of twenty but an average of 18 would be listed as having 9 runs on our sheet.
Average Score tells us where they are most likelyto get out. We'll use it as a probable score.
Balls Faced is of no concern as it is factored into the strike rate.
Strike Rate is very useful stat as we can use it to calculate the rate the player will score.
100s/50s/6s/4s are all factored into the average and strike rate so are not necessary for us.
So we are just keeping the player's Average and Strike Rate. We also check the Highest Score but don't keep it. We now need to boil it down to something useful. How many runs will they get and how many balls will they use to get it?
So a players batting should look like this:
Name 
Average 
Strike Rate 

Runs 
Balls 






Once we get the whole squad listed it's just a matter of waiting for the XI to be listed at the toss. Then we cut the list down to just those 11. Now obviously there will be more than the 120 balls available to a team in the scorecard we have set up, but this will be dealt with in the summary.
We can cut the record down further by removing numbers after we have finished with them. Once we have the Runs and Balls calculated we can remove the average and strike rate. We'll keep the player's name however as this is the first column of our stat sheet. So after cutting to the bare minimum we have:
Name 
Runs 
Balls 



Catches is really the only stat we can use to measure a players fielding. So it will be factored in.
Stumpings are, aside from only useful to wicketkeepers, not very helpful as a stat.
We'll take the number of catches and divide it by the number of games. It will most likely give a decimal place and we'll figure that's the odds he'll hang on to a catch during the game.
Let's make a few assumptions. The wicketkeeper is going to take a lot more catches than an ordinary fieldsman. While being a fair assumption, how do we factor in a team that has recruited two wicketkeepers? One of them will be in a standard fielding position where the catching stat will be deceptive. We'll deal with it by not worrying about it. It's fair to say if you fielded a team of all wicketkeepers the chance of any catch being dropped anywhere on the field is pretty slim. Bear in mind we are trying to fit a value to something that is very vague. The number of catches does not tell you how many were dropped, or even wether the captain will place that player where the ball is expected to be hit or simply covering a misfield in the infield.
So how much is a catch worth? Anyone who knows cricket can tell you catches win matches. We are going to assign an arbitrary amount. You can agree or disagree because the value of a catch is VERY subjective and can never be quantified. Personally I value a catch as 20 runs. We won't set a penalty for a low number of catches however, as then we would actually have to quantify bad fielding with just one stat, and that's stretching it a bit far.
So here's what we have:
Fielder 
Matches 
Catches 
Fielder Rating 
Run Value 





That's a lot of space.
The fielder rating covers the matches and catches fields, so we can calculate the former and drop the latter. The run value is a simple multiplication, so why don't we just put multiply it out after we add up the teams fielder ratings. While we're at it we can just call it 'fielding' since it basically summarises everything we calculate about fielding.
And since the name of the fielder will already be on the sheet we can shorten the fielding section down to just one field:
Fielding 

To conteract the batting, we need to see what the bowling team does against the average opposition.
Matches, Innings and Balls Bowled again are irrelevant as they just tell us how accurate our figures are, without adding to them. If you see a player with under 10 games you can expect to need to adjust their numbers during the season.
Runs and Wickets are factored into the average and strike rate so we can ignore this.
Best Bowling figures would be double counted if we used them as they are reflected in the players bowling average. They also are less useful than a batsmans top score as a batsman must continually not make mistakes to reach a top score, while a bowler can bowl garbage and then come back later and improve in the same innings.
5 wicket hauls fall into the same basket as best bowling figures in that they will be reflected in the players average anyway.
Average is the runs divided by wickets and tells us how often we can expect a wicket from this bowler.
Economy is the number of runs an over we expect from the bowler. We can use this to see how many runs will be conceded if the bowler bowls his full 4 overs.
The next step is to extrapolate some bowling figures from all this. Let's assume a bowler has 4 overs for a moment. We can multiply the economy by 4 to get the runs conceded. From here we divide the average into this number and get our number of wickets.
There are people who will roll their eyes at these numbers, and those same people will come back with a system either too complicated or one that includes a very subjective number, such as a "rating out of 10" which is arbitrarily given by them. We are trying to eliminate this subjectiveness so this is why we stick with such a simple method.
So we are simply left with:
Bowler 
Average 
Economy 

Runs/ 4 overs 
Wickets/ 4 overs 






Much like before we can cut out the the information we don't need anymore and finalise our bowling stats as:
Runs/4 overs 
Wickets/4 overs 

