14th April, 2018. Email: Sportsanalyticsadvantage@gmail.com Ten matches have now been completed in the 2018 IPL - the league table is starting to form, while both the supporters of teams and team management alike are starting to consider whether the big money spent at auction on certain players equated to good value. In the first ten matches, we are able to draw some conclusions, and here is a range of data from the 2018 edition of the IPL so far:-
So far in this year's IPL, we can see that overseas batsmen have done considerably better than their Indian counterparts, recording 26.67 runs per wicket (compared to 23.71) and striking at 150.37, as opposed to 126.63 for domestic players. However, Indian bowlers, averaging 25.50 runs per wicket compared to 28.82 for overseas bowlers, have an edge, with almost identical economy rates. Historically over the last couple of seasons in the IPL, as we discussed in our article here, overseas bowlers have had this similar economy rate to their domestic rivals, but a better average, so this year's 10 matches so far have flipped this on its head a little, while overseas batsmen had a marginally better average but a fair bit better strike rate than Indian batsmen. With this in mind, and the other data discussed in that article, it is clear that overseas players are generally better than domestic players, as is absolutely logical. On this basis, it's obviously a pre-requisite for any overseas player that they are better than the average player in their position - a concept which hasn't always been adhered to by T20 franchises. As with any auction and draft, signings ranged from the sublime to the ridiculous, and while most previews and analysis of tournaments tend to focus on players to watch - those players who are perceived to be good value with future upside - I want to look at some of the signings that teams made during the auction, that our algorithm would perceive as mistakes. Such an exercise is pretty interesting, in that this analysis often points to reasons as to why teams are struggling - even just several players with negative expectation in a team can lead to a significant decrease in a team's expected win percentage, and as has been mentioned numerous times on this website, it is not only imperative that the correct players are signed at auctions and drafts (given expected conditions and opposition) but also that the correct players are chosen by the team management for any given match. In addition, it's very easy to establish which players are world-class - we all know who the world-class players are, but understanding which players add negative value is much more different for anyone from the casual fan to commentators to team management. Today's match between the Mumbai Indians and the Delhi Daredevils highlighted this fact. Mumbai spinner Akila Dananjaya's data, according to our algorithm, is very poor indeed, and I'm amazed that he is picked up by T20 franchises, let alone IPL ones. Opponents Delhi included Trent Boult and Mohammed Shami in their team, and both have much worse T20 data than red-ball, and it would appear that their recruitment, as well as selection, was affected by bias from other formats. Both Boult and Dananjaya are overseas players, which as we've already discussed, should be better than the average player. In both cases, this is extremely questionable.  Prior to the start of the 2018 IPL, my algorithm established expected batting and bowling data for all the players in the competition, and the following batsmen (to clarify, bowling all-rounders and bowlers were not included in this filter) had both a mean batting average and batting strike rate deviation of 0.95 or below, based on the mean IPL figures from 2017 (25.29 average, 133.36 strike rate) - in effect, our algorithm established they were at least 5% below the average batsmen for both batting average and batting strike rate:-
These players look to be pretty questionable signings - all six are domestic players (it would be horrific if an overseas batsman was included in this list, given the scarceness of that resource) but given the depth of the domestic talent pool in India, which is such that I can give the names of dozens of better batsmen not signed by IPL franchises, it's not a ringing endorsement of the domestic player recruitment that these players were signed either. Looking at all-rounders, the following players were rated by our algorithm as having a mean deviation of 1.00 or below for all of their batting and bowling metrics - in effect, they were below the average batsman and bowler in all four mean deviation metrics:-
This list of below-average all-rounders is fascinating. We now see the addition of overseas players (replacement player Tom Curran) while some of the domestic players on the list may also of a surprise to some readers, with Hardik Pandya (he looks much better at 50 over cricket than T20 currently) and the declining Yuvraj Singh among the high-profile players in this below-average all-rounder list.  Finally, we can establish a list of bowlers who had a mean deviation of 0.95 or below, with our algorithm establishing that they were at least 5% below the average bowler for both bowling average and bowling economy rate (it's worth noting that some bowlers did not have a big enough data sample for my algorithm to assess, such as Shivam Mavi):-
The dozen players here contain four overseas bowlers (the aforementioned Boult and Dananjaya, as well as Boult's countryman, Mitchell McClenaghan, and Dananjaya's compatriot, Dushmantha Chameera), while the remainder of the list are domestic bowlers, with generally very poor bowling economy rates. However, several of the domestic players have international honours, which illustrate that national team selectors also have issues picking their best squads. Of the entire list of below-average batsmen, all-rounders and bowlers, players from the Delhi Daredevils (seven players) dominate the list, with Rajasthan Royals (six) and Mumbai Indians (five) following. Interestingly, this trio of franchises currently comprise the bottom three of the league table. Impressively, Royal Challengers Bangalore did not have a single player in the list. Now that we have established a comprehensive list of below-average players, it is interesting to see how they have fared so far in IPL 2018 - have their performances so far justified my low pre-tournament expectations of them?
So far, these players have recorded the following combined data:- Batting Average: 17.63 Batting Strike Rate: 93.38 Bowling Average: 34.62 Bowling Economy Rate: 9.64 Evidently, the combined data for these players is considerably worse than the average IPL data for this year (batting average 24.82, strike rate 135.21, bowling average 26.39, bowling economy 8.39) and while a number of these players have not been included in teams so far, players in this list who have been picked by franchises have hardly covered themselves in glory. Such situations need not be an issue with quality recruitment which focuses on data analysis. If this article has given you insight into the data that Sports Analytics Advantage can offer cricket franchises around the world in formulating draft or auction plans, please feel free to enquire for bespoke draft and auction strategies via sportsanalyticsadvantage@gmail.com. |