How Pre-Game Analytics Predicted Jersey’s Win Over Scotland
- T20 Analytics
- Jul 11
- 3 min read
Updated: 4 days ago
Data-driven insights behind one of associate cricket’s biggest upsets
The Hague | July 11, 2025
Jersey’s one-wicket win over Scotland stood out in the Europe Region Final. Scotland entered ranked #13 in T20Is with extensive World Cup experience; Jersey, an associate member from the Channel Islands, were the underdogs. Yet pre-game analytics suggested a path to victory ― and much of it unfolded as expected.
Rankings Context
Scotland’s record speaks for itself: three ODI World Cups, five T20 World Cups, and wins against Full Member nations such as Bangladesh and West Indies. Jersey, by contrast, are still establishing themselves at the international level. The gap in experience and ranking was significant, but the data indicated that certain conditions at The Hague could help close it.
Venue Intelligence
Predicted trends:
Par score: ~160
Restriction target when bowling first: ≤145
Toss recommendation: Bowl first (historical 60% win rate for chasing sides)
Outcome: Scotland’s 133/7 was below both the par total and the restriction target. By choosing to bowl first, Jersey matched the data-backed plan. Their bowlers contained boundaries effectively and made full use of the surface’s slower bounce.
Bowling Strategy
Historical data from Kampong CC showed:
Spinners concede fewer runs (7.2 RPO)
Pacers take wickets faster (SR ≈ 15)
Optimal mix: ~11 overs pace, 9 overs spin
Jersey’s attack used a 10:10 split, almost identical to the model.
Pace: Carlyon 3/26, Perchard 1/31, Gouge 0/15
Spin: Ward 2/24, Sumerauer 1/26, Blampied 0/9 (2 overs)
The spinners’ collective economy near six per over confirmed the plan’s value, and Scotland’s middle order never settled into rhythm.
Matchups and Batting Vulnerabilities
Pre-match data highlighted:
Mark Watt vs Charlie Brennan: bowler-favored ― Watt dismissed him again for 3.
Brad Currie: main threat ― Jersey played him cautiously, yielding 0/26 (4).
Top order vs spin: McMullen, Munsey, and Berrington had low strike rates against slower bowling. They produced 17 runs off 29 balls, contributing to a 13/3 collapse in the powerplay.
The match unfolded almost exactly as the numbers suggested.
Jersey’s Batting Response
Nick Greenwood’s 49 (36) anchored the chase, matching projections that identified him as Jersey’s most adaptable batter in these conditions. Harrison Carlyon added 15 off 10 at the top of the order and three wickets earlier in the innings ― a decisive all-round contribution.
At 129/9 chasing 134, execution ultimately decided the finish. Dominic Blampied and Elliot Miles managed the final runs with one ball remaining. Data set the framework; performance under pressure completed it.
What the Data Got Right
Venue call: Accurate ― Scotland finished below the defendable mark.
Bowling mix: Implemented as planned; spin proved decisive.
Matchups: Key duels followed historical trends.
Impact players: Carlyon and Greenwood delivered as forecast.
Our projections aligned closely with the actual outcome.
Lessons and Takeaway
Venue intelligence matters. Understanding surface behavior informs decisions on toss and target.
Historical matchups provide real value. Even limited data can highlight repeat patterns.
Balance and discipline make a difference. Jersey’s near-optimal bowling mix and economy kept a stronger opponent in check.
Analytics inform; players execute. Data creates structure; performance under pressure completes it.
For associate teams, matches like this show how analysis and preparation can offset differences in experience or resources. Jersey’s win at The Hague was a clear example of informed strategy meeting composed execution.
