IPL Bowling Review 2 – Performance Rating

In order to further review the performances of the bowlers in the 2017 IPL i have came up with a metric that takes various information such as number of wickets, strike rate, noumber of boundries conceded, dot balls. All things that are crucial to reviewing a bowler perfromance in the IPL.

bowler performance

The graph shows the top 43 bowlers in the 2017 IPL and there performance rating based on the factors already mentioned. Pawan Negi based on this metric was the best performing bowler which is surprising as 10 players took more wickets then him. However he was economical and bowled significantly less balls then the bowlers who took more wickets then him. This is why a metric like this is helpful as it helps you look past the wickets taken. At the other end of the scale is James Falkner who seems to have performed significantly worse then the next bowler. This seems to be down to low amount of wickets taken and high economy rate. Now this could be because of when he was bowling for instance if hes bowling in the powerplay for most of his overs.

Rplot

The plot above is the same plot however i have coloured the plot in order to show which team the bowler belongs too. There seems to be no big trend however the winners of the competition Mumbai have the most bowlers in the top 15 with 4.

Rplot2

The graph above i have now coloured the columns by the type of bowler. Nothing particularly stands out here. Overall this is a first attempt at reviewing the performance ratios. What would further develop this is maybe a look at this against there value in the auction. I think this can also be developed game by game and for batsmen as well.

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Analysing the Bowling Performances in the IPL

The IPL finished at the end of May with the Mumbai Indians winning the title on the last ball of the match against the now defunct Rising Pune Super Giant. I decided to take a new look at evaluating bowling performances. Currently bowlers in all cricket are judged based on the amount of wickets they have taken, their economy rate or their bowling average. I think there could be a new way of reviewing performances. If you take the batsmen average as an indication of how good the batsmen is the batsmen with higher averages must be harder wickets to take. Therefore if you record the average of the batsmen the bowler took the wicket of you can make a judgement of the quality of the bowling. Has the bowler took a lot of wickets but where they all lower order less quality batsmen or are they good at taking the top order wickets.

I have used this approach to review the bowling performances in the 2017 IPL. To qualify for this review the bowler had to have taken more then 5 wickets which left me with 44 bowlers. The first graph below shows the amount of wickets taken by bowler against the number of balls they bowled:

graphbowlers

Stand out performances from that graph are clearly Unadkat and Bhuvneshwar Kumar taking lots more wickets then anyone else who bowled a similar amount of balls. Sunil Narine looks to have had a significantly lower return of wickets then he should have done with  the amount of balls bowled. Now if we look at the quality of the batsmen the bowlers got out shown in the graph below:

graphbowlers2

As you can see our second ranked bowler based on wickets taken has one of the lowest average batting quality rating (have to come up with a better name!) at 18.45, suggesting that he often got his wickets from lower order batsmen. Kumar got his wickets at an Batsmen average of 22.33 which is a respectable value slightly lower then the average for all bowlers. The two highest bowlers where Chawler and Nadeem both only took 6 wickets but didn’t bowl many balls  (only 120 and 107 respectively). Would be interesting to know why they played only 6 games as they both looked to have troubled a lot of higher ranking batsmen.

That’s it for this first look as a way to review bowling performances. I think this can be explored a lot more and will definitely look to do that. The weakness of the method is the amount of games a batsmen has played as one that has played few will possibly have an unrepresentative average.