Lanka’s T20 Spinners: The Missing Aponso

Michael Roberts

Guided by the vague notion that the omission of Vandersay and the choice of Sandakan for the T20 series in South Africa was an error of some magnitude, I went for the statistics on all the leading Sri Lankan spinners in this format. There is a problem here however. The ESPNcricinfo style of statistics distinguish between T20Is and Twenty20. I assumed the former figure was restricted to international games and focused on the whole corpus of games because some players have had limited exposure at the international level.

Aponso  vandersay Vandersay

The key indicators are (A) Strike Rate ….. (b) Economy Rate…. (C) Average. My survey encompassed Amila Aponso, Sachitra Pathirana, Dilruwan Perera, Seekkuge Prasanna, Lakshan Sandakan, Sachitra Senanayake, Milinda Siriwardena, and Jeffrey Vandersay.

The Results

Surprise! Amila Aponso came on top in all three categories A, B and C and Vandersay was down the list among the also/rans in these three fields.  So let me set out the figures category by category (with bracketed figure indicating balls bowled and thus marking length of career)

Strike/Rate                           Econ/Rate                            Average

Aponso         13.4                Aponso          6.05                Aponso          13.5

Pathirana      15.0                S’nayake       6.46                Pathirana      18.69

Sandakan      17.5                Perera           6.70                S’nayake       21.49

S’nayake       10.9                Prasanna      6.8                  Perera           24.25

S’wardena    20.0                Vandersay    7.08                Sandakan      25.50

Perera           21.7                Pathirana      7.46                Prasanna      25.5

Prasanna     22.4                 S’wardena    7.91                S’wardena    26.39

Vandersay    28.8                Sandakan      8.74               Vandersay    34.00

This comparative set of figures should be complemented by attention to length of career marked by balls bowled: presented here by bracketed figures:  Amila Aponso (229), Sachitra Pathirana (736), Dilruwan Perera (1129), Seekkuge Prasanna (1611), Lakshan Sandakan (280), Sachitra Senanayake (1936), Milinda Siriwardena (860) and Jeffrey Vandersay (461).

Ideally one should also have a reckoner for fielding and throwing capabilities. I know that Prasanna and Senanayake are pretty nifty and useful in the field but have limited knowledge about the others. The absence of this guideline undermines my comparative exploration.

sandakan Sandakan in action in whitesaponso-wkt Aponso traps Faulkner


Why, then, is Aponso not in the T20 Squad. In surmise, I present a good reason in the Selector’s calculations. He is left-arm spinner in the same mould as Pathirana and a poor batsman. Pathirana has displaced Siriwardena in the ODI formats as a genuine allrounder and is a useful hand in the middle order around No. 7 or 8.

Seekkuge Prasanna provides a top-spinning option with the ability to hammer runs – though I have rarely seen him succeed in this role at international level as distinct from domestic shorter format games.

As a back-up spinner of the genuine leg-spinning variety the selectors have opted for Sandakan rather than Vandersay. While Sandakan pips the latter in the statistical comparison, I am impressed by Vandersay’s fighting mien. But, then, I have not seen much of Sandakan in the field (bar in one Test Match).

prasanna Prasanna dilruwan-perera Pereras-senanayake Senanayake

A NOTE: As a comaparative yardstick note the summaries re two of the newcomers in the South African T20 line-up,

Lungi Ngidi16th on the wicket charts in this season’s domestic T20 competition with nine wickets at 33.11 and an economy rate of 8.27

Dane Paterson:     Ninth on the wicket charts in last season’s domestic T20 competition with 12 wickets at 20.58 and an economy rate of 7.56; six wickets this season at 39.00 and an economy rate of 8.11

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Filed under performance, player selections, Sri Lanka Cricket, T20 Cricket, unusual statistics

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