Cricket and financial markets have a rich, intertwined history, from Vincent back to Waugh/Warne, Lillee/Marsh and Keith Miller. So, I don't think we necessarily need a new cricket market, but let's make one anyway, and refresh my financial maths and linear algebra at the same time. Cricket, especially its shortened forms, is seemingly becoming a batsman's game. Bats are bigger, fields are smaller, fielding and bowling restrictions make it difficult to pressure the batsmen, players are fitter and the game is more professional than it has ever been. The trend towards bigger scores is shown clearly in men's One-day International (ODI) cricket. The following chart shows the yearly average score each team scored when batting first in an ODI*, with the black line (ODIAll) being the average of all games in that year. The "Associate" line refers to Associate cricket teams that played games the International Cricket Council (ICC) deemed worthy enough to have ODI status, and also those World XI, Asia XI and Africa XI matches that were in vogue about 10 years ago and were also given ODI status. Individual Associate nations did not play enough games to create enough meaningful data for this analysis.ODI ScoresCreate line charts*Only innings that went for 50-overs, or where the team was bowled out, were counted so as to take out the influence of rain.In our financial market, each of the series above is a stock, whose value is that team's average ODI score batting first in that year. The ODIAll series is the index for this particular stock market (like the S&P 500 or All Ordinaries). The upward trend in ODIAll is clear, and the following shows ODIAll data with an exponential fit. An exponential fit is what you would expect if the stock was growing with continuously compounding interest. The fit is pretty good (R2 = 0.8). The other dots are the country data and show the scatter (and noise) in the data set. I've gone back to 1980, as before then there were few games played annually.Such trends are evident in other sports, but not all sports are as focused on increasing scores. Premier League football shows no such scoring trend, total home runs in Major League Baseball ebbs and flows depending on a number of factors including the amount of steroids being taken, but there has been a steady increase in strike outs over the last 20 years. Let's do some maths. What we want to do is determine in which teams we should invest. We don't necessarily want to invest in the teams that regularly produce the highest scores. We want to pick the teams that are improving - that is, their stock prices are going up so we'll get a good return. For instance, Australia has been dominant in ODI cricket for some time; it may not be a good investment if it can not continue to grow its already large yearly average. On the other hand, Associate teams are playing more ODI cricket and Bangladesh is ever improving, perhaps they would be better investments, although likely to be more risky than an established team. Maybe we'd be better off just buying the ODIAll Index.Inline with Modern Portfolio Theory, I used the methods in these two articles:Calculating the Efficient Frontier: Part 1 Portfolio optimization using the efficient frontier and capital market line in ExcelYes, I did it in Excel, and yes I realise that if I was any sort of data analyst I would have done it in R, but if you can't go 80% of the way towards solving the problem in Excel, it's not a problem worth solving.The following chart shows the average percentage return and standard deviation of each country's yearly stock price. On average, Australia increases its price by ~1%, with a standard deviation (risk) of 8%. Interestingly, South Africa, for a similar risk, has a ~2% return. Bangladesh is the BRIC of this market, rapidly improving over the last few years, but with a relatively high risk. The Associates are far too risky to invest in just yet.  To determine your portfolio, you don't