WASP (cricket Calculation Tool)
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Winning and Score Predictor (WASP) is a calculation tool used in
cricket Cricket is a bat-and-ball game played between two teams of eleven players on a field at the centre of which is a pitch with a wicket at each end, each comprising two bails balanced on three stumps. The batting side scores runs by striki ...
to predict scores and possible results of a limited overs match, e.g. One Day and
Twenty 20 Twenty20 (T20) is a shortened game format of cricket. At the professional level, it was introduced by the England and Wales Cricket Board (ECB) in 2003 for the inter-county competition. In a Twenty20 game, the two teams have a single innin ...
matches. The prediction is based upon factors like the ease of scoring on the day according to the pitch, weather and boundary size. For the team batting first, it gives the prediction of the final total. For the team batting second, it gives the probability of the chasing team winning, although it does not just take the match situation into equation. Predictions are based on the average team playing against the average team in those conditions. The models are based on a database of all non-shortened
One Day International A One Day International (ODI) is a form of limited overs cricket, played between two teams with international status, in which each team faces a fixed number of overs, currently 50, with the game lasting up to 9 hours. The Cricket World C ...
(ODI) matches and Twenty20 games played between top-eight countries since late 2006 (slightly further back for Twenty20 games). The batting-first model estimates the additional runs likely to be scored as a function of the number of balls and wickets remaining. The batting-second model estimates the probability of winning as a function of balls and wickets remaining, runs scored to date, and the target score. Projected score or required run-rate will not qualitatively show the real picture as they fail to take into the account the quality of the batting team and the quality of the bowling attack. WASP is a very good quantitative parameter.


History

The WASP technique is a product of some extensive research from PhD graduate Dr Scott Brooker and his supervisor Dr Seamus Hogan at the
University of Canterbury The University of Canterbury ( mi, Te Whare Wānanga o Waitaha; postnominal abbreviation ''Cantuar.'' or ''Cant.'' for ''Cantuariensis'', the Latin name for Canterbury) is a public research university based in Christchurch, New Zealand. It was ...
(UC) in Christchurch, New Zealand. They worked on this project for four years and started after they received a phone call from the university's economics department asking them to investigate alternatives to the Duckworth–Lewis method. WASP was first introduced to the public by Sky Sport New Zealand in November 2012 during Auckland's
HRV Cup The Men's Super Smash, currently named the Dream11 Super Smash for sponsorship purposes until 2026, is a men's domestic Twenty20 cricket competition in New Zealand. Since the 2018–19 season, the competition runs alongside the Women's Super Sma ...
Twenty20 game against Wellington. SInce 2018, the underlying WASP system has been owned b
NV Play
a global cricket technology company based in New Zealand.
NV Play
have subsequently extended the WASP tool (in partnership with Dr Scott Brooker, one of the original WASP creators) to include the concept of pressure, and have developed a range of enhanced player contribution metrics to support high performance programmes. WASP is now deeply embedded i
NV Play Cricket
NV's flagship cricket technology platform, and is available to all high end recreational & professional cricketers.


Theory

The WASP system is grounded in the theory of dynamic programming. It looks at data from past matches and estimates the probability of runs and wickets in each game situation, and works backwards to calculate the total runs or probability of winning in any situation. This is how Dr Seamus Hogan – one of the creators of WASP – described the system: Let ''V''(''b'',''w'') be the expected additional runs for the rest of the innings when ''b'' (legitimate) balls have been bowled and ''w'' wickets have been lost, and let ''r''(''b'',''w'') and ''p''(''b'',''w'') be, respectively, the estimated expected runs and the probability of a wicket on the next ball in that situation. We can then write, : V(b,w) = r(b,w) + p(b,w) V(b+1,w+1) + (1-p(b,w))V(b+1,w) Since ''V''(''b*'',''w'')=0 where ''b''* equals the maximum number of legitimate deliveries allowed in the innings (300 in a 50 over game), we can solve the model backwards. This means that the estimates for ''V''(''b'',''w'') in rare situations depends only slightly on the estimated runs and probability of a wicket on that ball, and mostly on the values of ''V''(''b'' + 1,''w'') and ''V''(''b'' + 1,''w'' + 1), which will be mostly determined by thick data points. The batting second model is a bit more complicated, but uses essentially the same logic.


Drawbacks

If a batsman gets retired hurt, the model will not work well as it does not know the position in which the retired hurt batsman will come to bat again. This happened in a match between England and New Zealand, as injured Martin Guptill came to the crease again in the ninth position and gave a staggering performance which is unusual for a ninth position batsman and helped his team to win the match.


References

{{Reflist Prediction Dynamic programming Cricket terminology