League Two 2025/2026 End-of-Season Analysis

Season Overview

This season in League Two, a total of 557 fixtures were analysed, with 461 of those having valid model signals. The overall signal hit rate stood at 50.6%, reflecting the competitive nature of the league and the difficulty in consistently predicting outcomes.

Signal Performance

The performance of signals was analysed across home, draw, and away categories, with each signal rated on a three-star system (★★★, ★★, ★). The highest hit rates were observed in ★★ home and away signals, both achieving a 57.5% hit rate. ★★★ home signals also performed well with a 60.0% hit rate, while ★★★ away signals had a 50.0% hit rate. Draw signals, across all ratings, had the lowest hit rates, with only a 33.3% success rate.

| Signal Type | Stars | Bets | Wins | Draws | Hit Rate |

|-------------|-------|------|------|-------|----------|

| Home | ★★★ | 15 | 9 | 5 | 60.0% |

| Home | ★★ | 167 | 96 | 41 | 57.5% |

| Home | ★ | 130 | 53 | 35 | 40.8% |

| Draw | ★ | 9 | 3 | | 33.3% |

| Away | ★★★ | 14 | 7 | 2 | 50.0% |

| Away | ★★ | 80 | 46 | 19 | 57.5% |

| Away | ★ | 46 | 19 | 12 | 41.3% |

Match Winner P&L

Betting on all available signals resulted in a 53.3% win rate, generating a P&L of +21.51 units and an ROI of +8.37%. Filtering to only value bets (edge > 0) improved the ROI significantly to +27.53%, though at the cost of fewer bets and a lower P&L of +19.27 units. Filtering to value bets does add meaningful edge, but with reduced bet volume.

| Betting Approach | Bets | Wins | Win Rate | P&L | ROI |

|-----------------------|------|------|----------|---------|---------|

| Back all signals | 257 | 137 | 53.3% | +21.51 | +8.37% |

| Value bets only | 70 | 33 | 47.1% | +19.27 | +27.53% |

BTTS by Probability Bracket

The actual BTTS rate was 52.2%, compared to the V12 model average of 53.0%. Betting on all BTTS signals across all probability brackets resulted in an overall negative P&L of -34.51 units and an ROI of -11.3%. Filtering to value bets improved the ROI slightly to -10.4%.

| Bracket | Fixtures | Hit% | Back All Bets | Back All P&L | Back All ROI | Value Bets | Value P&L | Value ROI |

|---------------|----------|------|---------------|--------------|--------------|------------|-----------|-----------|

| <45% | 12 | 41.7%| 12 | -2.50 | -20.8% | 0 | - | - |

| 45-50% | 72 | 48.6%| 72 | -6.77 | -9.4% | 4 | +0.40 | 10.0% |

| 50-55% | 123 | 52.0%| 123 | -5.87 | -4.8% | 35 | -1.01 | -2.9% |

| 55-60% | 78 | 39.7%| 78 | -22.04 | -28.3% | 44 | -12.10 | -27.5% |

| 60-65% | 18 | 61.1%| 18 | +1.41 | 7.8% | 17 | +0.81 | 4.8% |

| 65-70% | 2 | 100% | 2 | +1.26 | 63.0% | 2 | +1.26 | 63.0% |

| 70%+ | 0 | 0% | 0 | - | - | 0 | - | - |

| Total | 305 | | 305 | -34.51 | -11.3% | 102 | -10.64| -10.4%|

Over 2.5 by Probability Bracket

The actual Over 2.5 rate was 47.9%, compared to the V12 model average of 50.3%. Betting on all Over 2.5 signals resulted in an overall negative P&L of -25.76 units and an ROI of -8.4%. Filtering to value bets slightly improved the ROI to -7.8%.

| Bracket | Fixtures | Hit% | Back All Bets | Back All P&L | Back All ROI | Value Bets | Value P&L | Value ROI |

|---------------|----------|------|---------------|--------------|--------------|------------|-----------|-----------|

| <45% | 54 | 48.1%| 54 | -1.41 | -2.6% | 2 | +0.38 | 19.0% |

| 45-50% | 101 | 50.5%| 101 | -1.01 | -1.0% | 17 | +2.65 | 15.6% |

| 50-55% | 86 | 44.2%| 86 | -12.53 | -14.6% | 51 | -8.40 | -16.5% |

| 55-60% | 53 | 41.5%| 53 | -10.65 | -20.1% | 43 | -4.10 | -9.5% |

| 60-65% | 9 | 44.4%| 9 | -1.76 | -19.6% | 9 | -1.76 | -19.6% |

| 65-70% | 1 | 100% | 1 | +0.65 | 65.0% | 1 | +0.65 | 65.0% |

| 70%+ | 1 | 100% | 1 | +0.95 | 95.0% | 1 | +0.95 | 95.0% |

| Total | 305 | | 305 | -25.76 | -8.4% | 124 | -9.63 | -7.8% |

Team Analysis

Several teams over-performed relative to their expected goals (xG), with Milton Keynes Dons leading the pack with 22.47 goals above their xG. Conversely, Crawley Town under-performed the most, scoring 3.44 goals fewer than their xG.

Over-performers (scored above xG)

| Team | Goals | xG | Goal Difference | Wins/Draws across Fixtures |

|-------------------|-------|------|-----------------|-----------------------------|

| Milton Keynes Dons| 86 | 63.5 | +22.47 | 24W/14D across 46 fixtures |

| Grimsby | 75 | 57.9 | +17.11 | 22W/13D across 48 fixtures |

| Notts County | 78 | 62.3 | +15.74 | 26W/9D across 49 fixtures |

| Barnet | 70 | 57.0 | +12.96 | 21W/13D across 46 fixtures |

| Chesterfield | 71 | 59.2 | +11.80 | 21W/17D across 48 fixtures |

Under-performers (scored below xG)

| Team | Goals | xG | Goal Difference | Wins/Draws across Fixtures |

|-------------------|-------|------|-----------------|-----------------------------|

| Crawley Town | 44 | 47.4 | -3.44 | 8W/16D across 46 fixtures |

| Shrewsbury | 42 | 45.0 | -2.97 | 13W/10D across 46 fixtures |

| Barrow | 45 | 47.7 | -2.68 | 9W/9D across 46 fixtures |

Signal Hit Rates by Team

| Team | Signals Correct | Total Signals | Hit Rate |

|-------------------|-----------------|---------------|-----------|

| Bristol Rovers | 9 | 11 | 81.8% |

| Bromley | 18 | 29 | 62.1% |

| Swindon Town | 17 | 29 | 58.6% |

| Cambridge United | 17 | 29 | 58.6% |

| Chesterfield | 12 | 21 | 57.1% |

| Notts County | 17 | 30 | 56.7% |

| Tranmere | 7 | 13 | 53.8% |

| Milton Keynes Dons | 18 | 34 | 52.9% |

Players to Follow

Several standout players emerged this season based on their shot creation, efficiency, and underlying numbers.

Top Scorers

| Player | Goals | Assists | Shots on Target | Minutes Played |

|---------------------|-------|---------|-----------------|----------------|

| Aaron Drinan | 22 | 5 | 44/71 | 3339 |

| Jaze Kabia | 18 | 2 | 39/61 | 3026 |

| Michael Cheek | 16 | 3 | 35/62 | 2901 |

| Callum Paterson | 16 | 7 | 29/58 | 2815 |

| Daniel Kanu | 15 | 2 | 45/75 | 3147 |

| Alassana Jatta | 15 | 3 | 35/49 | 2588 |

| Isaac Hutchinson | 15 | 3 | 31/68 | 3068 |

| Kabongo Tshimanga | 15 | 1 | 25/41 | 2842 |

Top Assisters

| Player | Assists | Goals | Minutes Played |

|---------------------|---------|-------|----------------|

| Tommi O'Reilly | 11 | 6 | 3610 |

| Liam Mandeville | 11 | 6 | 2673 |

| Charles Vernam | 10 | 10 | 2899 |

| Mitchell Pinnock | 10 | 2 | 3994 |

| Shaun Whalley | 9 | 5 | 2736 |

| Liam Kelly | 9 | 1 | 3457 |

Key Takeaways